TY  - JOUR
AU  - Marković, Veljko
AU  - Jakovljević, Živana
AU  - Budak, Igor
PY  - 2022
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/91
AB  - 3D scanning devices are traditionally employed in reverse engineering tasks that can be carried out semi-automatically, with user assistance. However, their application in manufacturing process control requires automatic point cloud segmentation and extraction of geometric primitives. In this paper, we propose a method for automatic recognition of planes and cylinders (most frequently encountered geometric primitives in mechanical engineering) from unstructured point clouds. The method is based on the scatter of data during least squares fitting of second order surfaces. It consists of three phases and the first phase represents automatic point cloud segmentation. The second phase deals with merging of over-segmented regions and surfaces parameters estimation, whereas the final phase provides extraction of recognized geometric primitives. The method is experimentally verified using three real-world case studies, and its performances are compared with two state of the art recognition algorithms. The results have shown that the proposed method outperforms alternative approaches in terms of appropriately recognized planes and cylinders without surface type confusion, as well as when the recognition of non-existent primitives is considered. In addition, the method determines surfaces parameters with high accuracy.
PB  - Springer, New York
T2  - Visual Computer
T1  - Automatic recognition of cylinders and planes from unstructured point clouds
EP  - 4352
SP  - 4329
VL  - 38
DO  - 10.1007/s00371-021-02299-9
ER  - 

@article{
author = "Marković, Veljko and Jakovljević, Živana and Budak, Igor",
year = "2022",
abstract = "3D scanning devices are traditionally employed in reverse engineering tasks that can be carried out semi-automatically, with user assistance. However, their application in manufacturing process control requires automatic point cloud segmentation and extraction of geometric primitives. In this paper, we propose a method for automatic recognition of planes and cylinders (most frequently encountered geometric primitives in mechanical engineering) from unstructured point clouds. The method is based on the scatter of data during least squares fitting of second order surfaces. It consists of three phases and the first phase represents automatic point cloud segmentation. The second phase deals with merging of over-segmented regions and surfaces parameters estimation, whereas the final phase provides extraction of recognized geometric primitives. The method is experimentally verified using three real-world case studies, and its performances are compared with two state of the art recognition algorithms. The results have shown that the proposed method outperforms alternative approaches in terms of appropriately recognized planes and cylinders without surface type confusion, as well as when the recognition of non-existent primitives is considered. In addition, the method determines surfaces parameters with high accuracy.",
publisher = "Springer, New York",
journal = "Visual Computer",
title = "Automatic recognition of cylinders and planes from unstructured point clouds",
pages = "4352-4329",
volume = "38",
doi = "10.1007/s00371-021-02299-9"
}

Marković, V., Jakovljević, Ž.,& Budak, I.. (2022). Automatic recognition of cylinders and planes from unstructured point clouds. in Visual Computer
Springer, New York., 38, 4329-4352.
https://doi.org/10.1007/s00371-021-02299-9

Marković V, Jakovljević Ž, Budak I. Automatic recognition of cylinders and planes from unstructured point clouds. in Visual Computer. 2022;38:4329-4352.
doi:10.1007/s00371-021-02299-9 .

Marković, Veljko, Jakovljević, Živana, Budak, Igor, "Automatic recognition of cylinders and planes from unstructured point clouds" in Visual Computer, 38 (2022):4329-4352,
https://doi.org/10.1007/s00371-021-02299-9 . .

TY  - JOUR
AU  - Marković, Veljko
AU  - Jakovljević, Živana
AU  - Miljković, Zoran
PY  - 2019
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/3128
AB  - Contemporary three-dimensional (3D) scanning devices are characterized by high speed and resolution. They provide dense point clouds that contain abundant data about scanned objects and require computationally intensive and time consuming processing. On the other hand, point clouds usually contain a large amount of redundant data that carry little or no additional information about scanned object geometry. To facilitate further analysis and extraction of relevant information from point cloud, as well as faster transfer of data between different computational devices, it is rational to carry out its simplification at an early stage of the processing. However, the reduction of data during simplification has to ensure high level of information contents preservation; simplification has to be feature sensitive. In this paper we propose a method for feature sensitive simplification of 3D point clouds that is based on epsilon insensitive support vector regression (epsilon-SVR). The proposed method is intended for structured point clouds. It exploits the flatness property of epsilon-SVR for effective recognition of points in high curvature areas of scanned lines. The points from these areas are kept in simplified point cloud along with a reduced number of points from flat areas. In addition, the proposed method effectively detects the points in the vicinity of sharp edges without additional processing. Proposed simplification method is experimentally verified using three real world case studies. To estimate the quality of the simplification, we employ non-uniform rational b-splines fitting to initial and reduced scan lines.
PB  - Univ Osijek, Tech Fac, Slavonski Brod
T2  - Tehnički vjesnik
T1  - Feature Sensitive Three-Dimensional Point Cloud Simplification using Support Vector Regression
EP  - 994
IS  - 4
SP  - 985
VL  - 26
DO  - 10.17559/TV-20180328175336
ER  - 

@article{
author = "Marković, Veljko and Jakovljević, Živana and Miljković, Zoran",
year = "2019",
abstract = "Contemporary three-dimensional (3D) scanning devices are characterized by high speed and resolution. They provide dense point clouds that contain abundant data about scanned objects and require computationally intensive and time consuming processing. On the other hand, point clouds usually contain a large amount of redundant data that carry little or no additional information about scanned object geometry. To facilitate further analysis and extraction of relevant information from point cloud, as well as faster transfer of data between different computational devices, it is rational to carry out its simplification at an early stage of the processing. However, the reduction of data during simplification has to ensure high level of information contents preservation; simplification has to be feature sensitive. In this paper we propose a method for feature sensitive simplification of 3D point clouds that is based on epsilon insensitive support vector regression (epsilon-SVR). The proposed method is intended for structured point clouds. It exploits the flatness property of epsilon-SVR for effective recognition of points in high curvature areas of scanned lines. The points from these areas are kept in simplified point cloud along with a reduced number of points from flat areas. In addition, the proposed method effectively detects the points in the vicinity of sharp edges without additional processing. Proposed simplification method is experimentally verified using three real world case studies. To estimate the quality of the simplification, we employ non-uniform rational b-splines fitting to initial and reduced scan lines.",
publisher = "Univ Osijek, Tech Fac, Slavonski Brod",
journal = "Tehnički vjesnik",
title = "Feature Sensitive Three-Dimensional Point Cloud Simplification using Support Vector Regression",
pages = "994-985",
number = "4",
volume = "26",
doi = "10.17559/TV-20180328175336"
}

Marković, V., Jakovljević, Ž.,& Miljković, Z.. (2019). Feature Sensitive Three-Dimensional Point Cloud Simplification using Support Vector Regression. in Tehnički vjesnik
Univ Osijek, Tech Fac, Slavonski Brod., 26(4), 985-994.
https://doi.org/10.17559/TV-20180328175336

Marković V, Jakovljević Ž, Miljković Z. Feature Sensitive Three-Dimensional Point Cloud Simplification using Support Vector Regression. in Tehnički vjesnik. 2019;26(4):985-994.
doi:10.17559/TV-20180328175336 .

Marković, Veljko, Jakovljević, Živana, Miljković, Zoran, "Feature Sensitive Three-Dimensional Point Cloud Simplification using Support Vector Regression" in Tehnički vjesnik, 26, no. 4 (2019):985-994,
https://doi.org/10.17559/TV-20180328175336 . .

TY  - CONF
AU  - Marković, Veljko
AU  - Jakovljević, Živana
AU  - Budak, Igor
PY  - 2018
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/5221
AB  - U radu se predlaže metod za prepoznavanje cilindara i ravni u nestruktuiranim oblacima tačaka. Predloženi proces prepoznavanja se može podeliti u tri osnovne faze. Prvu fazu predstavlja automatska segmentacija širenjem regiona počev od jedne karakteristične tačke. Kriterijumi širenja regiona zasnovani su na osobinama singularnosti informacione matrice sistema kao i pripadnosti tačaka površi čiji su parametri estimirani metodom najmanjih kvadrata. Druga faza algoritma se odnosi na grupisanje presegmentiranih oblasti i estimaciju parametara prepoznatih cilindara i ravni. Dobre performanse ovoj fazi obezbeđuje upotreba unapređenog algoritma robusnog prepoznavanja cilindara iz oblaka tačaka kao i uvođenje procesa precizne estimacije parametara ravni. Na samom kraju, odnosno u trećoj fazi procesa upotrebom predloženog algoritma vrši se ponovna obrada celokupnog polaznog oblaka tačaka u cilju ekstrakcije prepoznatih primitiva i obezbeđivanja preciznih krajnjih rezultata. Predloženi metod je pre svega namenjen prepoznavanju cilindara i ravni u oblacima tačaka koji reprezentuju određene mašinske delove, pa je u skladu sa tim i eksperimentalno verifikovan na većem broju odgovarajućih sintetizovanih oblaka.
C3  - 41. JUPITER konferencija, Zbornik radova
T1  - Prepoznavanje cilindara i ravni u trodimenzionim oblacima tačaka
EP  - 2.18
SP  - 2.9
UR  - https://hdl.handle.net/21.15107/rcub_machinery_5221
ER  - 

@conference{
author = "Marković, Veljko and Jakovljević, Živana and Budak, Igor",
year = "2018",
abstract = "U radu se predlaže metod za prepoznavanje cilindara i ravni u nestruktuiranim oblacima tačaka. Predloženi proces prepoznavanja se može podeliti u tri osnovne faze. Prvu fazu predstavlja automatska segmentacija širenjem regiona počev od jedne karakteristične tačke. Kriterijumi širenja regiona zasnovani su na osobinama singularnosti informacione matrice sistema kao i pripadnosti tačaka površi čiji su parametri estimirani metodom najmanjih kvadrata. Druga faza algoritma se odnosi na grupisanje presegmentiranih oblasti i estimaciju parametara prepoznatih cilindara i ravni. Dobre performanse ovoj fazi obezbeđuje upotreba unapređenog algoritma robusnog prepoznavanja cilindara iz oblaka tačaka kao i uvođenje procesa precizne estimacije parametara ravni. Na samom kraju, odnosno u trećoj fazi procesa upotrebom predloženog algoritma vrši se ponovna obrada celokupnog polaznog oblaka tačaka u cilju ekstrakcije prepoznatih primitiva i obezbeđivanja preciznih krajnjih rezultata. Predloženi metod je pre svega namenjen prepoznavanju cilindara i ravni u oblacima tačaka koji reprezentuju određene mašinske delove, pa je u skladu sa tim i eksperimentalno verifikovan na većem broju odgovarajućih sintetizovanih oblaka.",
journal = "41. JUPITER konferencija, Zbornik radova",
title = "Prepoznavanje cilindara i ravni u trodimenzionim oblacima tačaka",
pages = "2.18-2.9",
url = "https://hdl.handle.net/21.15107/rcub_machinery_5221"
}

Marković, V., Jakovljević, Ž.,& Budak, I.. (2018). Prepoznavanje cilindara i ravni u trodimenzionim oblacima tačaka. in 41. JUPITER konferencija, Zbornik radova, 2.9-2.18.
https://hdl.handle.net/21.15107/rcub_machinery_5221

Marković V, Jakovljević Ž, Budak I. Prepoznavanje cilindara i ravni u trodimenzionim oblacima tačaka. in 41. JUPITER konferencija, Zbornik radova. 2018;:2.9-2.18.
https://hdl.handle.net/21.15107/rcub_machinery_5221 .

Marković, Veljko, Jakovljević, Živana, Budak, Igor, "Prepoznavanje cilindara i ravni u trodimenzionim oblacima tačaka" in 41. JUPITER konferencija, Zbornik radova (2018):2.9-2.18,
https://hdl.handle.net/21.15107/rcub_machinery_5221 .

TY  - JOUR
AU  - Marković, Veljko
AU  - Jakovljević, Živana
PY  - 2017
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/2645
AB  - U određenim oblastima industrije postoji potreba za generisanjem kompjuterskih modela objekata samo na osnovu njihove fizičke realizacije, a bez unapred poznatih konstrukcionih ili tehnoloških informacija. Pri realizaciji ovakvih zahteva istaknuto mesto zauzimaju tzv. tehnike reverznog inženjerstva geometrijskih modela. Bitnu fazu primene navedenih tehnika predstavlja prepoznavanje geometrijskih primitiva od kojih se posmatrani objekat sastoji. U ovom radu predstavljen je metod za segmentaciju i prepoznavanje G1 kontinualnih površina koje su u skenirnim linijama struktuiranog oblaka predstavljene eliptičnim segmentima. Predloženi algoritam je pre svega namenjen za prepoznavanje eliptičkih cilindara, elipsoida i eliptičkih torusa, ali se u zavisnosti od načina skeniranja dela, može koristiti i za prepoznavanje još nekih površi drugog reda. Proces segmentacije je zasnovan na prepoznavanju eliptičkih segmenata u skeniranim linijama, a na osnovu osobina singulariteta informacione matrice pri regresionoj analizi metodom najmanjih kvadrata. Verifikacija predloženog metoda je izvršena procesiranjem tri sintetizovana, kao i jednog realnog oblaka tačaka.
AB  - This paper presents a method for recognition of surfaces represented by elliptical segments in structured three dimensional (3D) point clouds. The method is based on direct least squares fitting of ellipses in scanned lines. By recognizing elliptical segments in both directions of structured cloud it is possible to efficiently allocate G1 (and higher) continuous regions which represent a certain class of surfaces. The proposed method is primarily developed for recognition of elliptical cylinders and ellipsoids, including cylinders and spheres. Depending on scanning mode, the method can be employed for recognition of other second degree surfaces like cones. Besides, as presented in the paper, the method can be utilized for recognition of certain class of higher degree surfaces such as elliptical tori. The proposed method is experimentally verified using several synthesized point clouds as well as using a real world case study.
PB  - Univerzitet u Beogradu - Mašinski fakultet, Beograd
T2  - FME Transactions
T1  - Prepoznvanje jedne klase površi u struktuiranom oblaku tačaka
T1  - Recognition of one class of surfaces from structured point cloud
EP  - 490
IS  - 4
SP  - 481
VL  - 45
DO  - 10.5937/fmet1704481M
ER  - 

@article{
author = "Marković, Veljko and Jakovljević, Živana",
year = "2017",
abstract = "U određenim oblastima industrije postoji potreba za generisanjem kompjuterskih modela objekata samo na osnovu njihove fizičke realizacije, a bez unapred poznatih konstrukcionih ili tehnoloških informacija. Pri realizaciji ovakvih zahteva istaknuto mesto zauzimaju tzv. tehnike reverznog inženjerstva geometrijskih modela. Bitnu fazu primene navedenih tehnika predstavlja prepoznavanje geometrijskih primitiva od kojih se posmatrani objekat sastoji. U ovom radu predstavljen je metod za segmentaciju i prepoznavanje G1 kontinualnih površina koje su u skenirnim linijama struktuiranog oblaka predstavljene eliptičnim segmentima. Predloženi algoritam je pre svega namenjen za prepoznavanje eliptičkih cilindara, elipsoida i eliptičkih torusa, ali se u zavisnosti od načina skeniranja dela, može koristiti i za prepoznavanje još nekih površi drugog reda. Proces segmentacije je zasnovan na prepoznavanju eliptičkih segmenata u skeniranim linijama, a na osnovu osobina singulariteta informacione matrice pri regresionoj analizi metodom najmanjih kvadrata. Verifikacija predloženog metoda je izvršena procesiranjem tri sintetizovana, kao i jednog realnog oblaka tačaka., This paper presents a method for recognition of surfaces represented by elliptical segments in structured three dimensional (3D) point clouds. The method is based on direct least squares fitting of ellipses in scanned lines. By recognizing elliptical segments in both directions of structured cloud it is possible to efficiently allocate G1 (and higher) continuous regions which represent a certain class of surfaces. The proposed method is primarily developed for recognition of elliptical cylinders and ellipsoids, including cylinders and spheres. Depending on scanning mode, the method can be employed for recognition of other second degree surfaces like cones. Besides, as presented in the paper, the method can be utilized for recognition of certain class of higher degree surfaces such as elliptical tori. The proposed method is experimentally verified using several synthesized point clouds as well as using a real world case study.",
publisher = "Univerzitet u Beogradu - Mašinski fakultet, Beograd",
journal = "FME Transactions",
title = "Prepoznvanje jedne klase površi u struktuiranom oblaku tačaka, Recognition of one class of surfaces from structured point cloud",
pages = "490-481",
number = "4",
volume = "45",
doi = "10.5937/fmet1704481M"
}

Marković, V.,& Jakovljević, Ž.. (2017). Prepoznvanje jedne klase površi u struktuiranom oblaku tačaka. in FME Transactions
Univerzitet u Beogradu - Mašinski fakultet, Beograd., 45(4), 481-490.
https://doi.org/10.5937/fmet1704481M

Marković V, Jakovljević Ž. Prepoznvanje jedne klase površi u struktuiranom oblaku tačaka. in FME Transactions. 2017;45(4):481-490.
doi:10.5937/fmet1704481M .

Marković, Veljko, Jakovljević, Živana, "Prepoznvanje jedne klase površi u struktuiranom oblaku tačaka" in FME Transactions, 45, no. 4 (2017):481-490,
https://doi.org/10.5937/fmet1704481M . .

TY  - JOUR
AU  - Jakovljević, Živana
AU  - Marković, Veljko
AU  - Živanović, Saša
PY  - 2016
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/5082
AB  - This paper presents a method for recognition of second order surfaces (quadrics) from point clouds containing information about scanned rotational parts. The method is region growing method that exploits the scatter of data during least squares fitting of quadrics as a region growing criterion. The presented procedure is convenient for segmentation of regions with high (G1 or higher) continuity. Besides, the region seed point is automatically selected which is its comparative advantage to a number of existing methods. The applicability of the proposed method is evaluated using two case studies; the first case study refers to a synthesized signal, and the second presents the applicability of the method on a real world example.
PB  - Faculty of Technical Sciences, Department of Production Engineering
T2  - Journal of Production Engineering
T1  - Recognition of quadrics from 3d point clouds generated by scanning of rotational parts
EP  - 68
IS  - 1
SP  - 65
VL  - 19
UR  - https://hdl.handle.net/21.15107/rcub_machinery_5082
ER  - 

@article{
author = "Jakovljević, Živana and Marković, Veljko and Živanović, Saša",
year = "2016",
abstract = "This paper presents a method for recognition of second order surfaces (quadrics) from point clouds containing information about scanned rotational parts. The method is region growing method that exploits the scatter of data during least squares fitting of quadrics as a region growing criterion. The presented procedure is convenient for segmentation of regions with high (G1 or higher) continuity. Besides, the region seed point is automatically selected which is its comparative advantage to a number of existing methods. The applicability of the proposed method is evaluated using two case studies; the first case study refers to a synthesized signal, and the second presents the applicability of the method on a real world example.",
publisher = "Faculty of Technical Sciences, Department of Production Engineering",
journal = "Journal of Production Engineering",
title = "Recognition of quadrics from 3d point clouds generated by scanning of rotational parts",
pages = "68-65",
number = "1",
volume = "19",
url = "https://hdl.handle.net/21.15107/rcub_machinery_5082"
}

Jakovljević, Ž., Marković, V.,& Živanović, S.. (2016). Recognition of quadrics from 3d point clouds generated by scanning of rotational parts. in Journal of Production Engineering
Faculty of Technical Sciences, Department of Production Engineering., 19(1), 65-68.
https://hdl.handle.net/21.15107/rcub_machinery_5082

Jakovljević Ž, Marković V, Živanović S. Recognition of quadrics from 3d point clouds generated by scanning of rotational parts. in Journal of Production Engineering. 2016;19(1):65-68.
https://hdl.handle.net/21.15107/rcub_machinery_5082 .

Jakovljević, Živana, Marković, Veljko, Živanović, Saša, "Recognition of quadrics from 3d point clouds generated by scanning of rotational parts" in Journal of Production Engineering, 19, no. 1 (2016):65-68,
https://hdl.handle.net/21.15107/rcub_machinery_5082 .

TY  - CONF
AU  - Jakovljević, Živana
AU  - Marković, Veljko
AU  - Puzović, Radovan
AU  - Majstorović, Vidosav D.
PY  - 2016
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/2388
AB  - Within cyber physical production systems 3D vision as a source of information from real-world provides enormous possibilities. While the hardware of contemporary 3D scanners is characterized by high speed along with high resolution and accuracy, there is a lack of real-time online data processing algorithms that would give certain elements of intelligence to the sensory system. Critical elements of data processing software are efficient, real-time applicable methods for fully automatic recognition of high level geometric primitives from point cloud (surface segmentation and fitting). This paper presents a method for recognition of one class of quadrics from 3D point clouds, in particular for recognition of cylinders, elliptical cylinders and ellipsoids. The method is based on the properties of scatter matrix during direct least squares fitting of ellipsoids. Presented recognition procedure can be employed for segmentation of regions with G1 or higher continuity, and this is its comparative advantage to similar methods. The applicability of the method is illustrated and experimentally verified using two case studies. First case study refers to a synthesized, and the second to a real-world scanned point cloud.
PB  - Elsevier B.V.
C3  - Procedia CIRP - 49th CIRP Conference on Manufacturing Systems (CIRP-CMS 2016)
T1  - Recognition of one class of quadrics from 3D point clouds
EP  - 297
SP  - 292
VL  - 57
DO  - 10.1016/j.procir.2016.11.051
ER  - 

@conference{
author = "Jakovljević, Živana and Marković, Veljko and Puzović, Radovan and Majstorović, Vidosav D.",
year = "2016",
abstract = "Within cyber physical production systems 3D vision as a source of information from real-world provides enormous possibilities. While the hardware of contemporary 3D scanners is characterized by high speed along with high resolution and accuracy, there is a lack of real-time online data processing algorithms that would give certain elements of intelligence to the sensory system. Critical elements of data processing software are efficient, real-time applicable methods for fully automatic recognition of high level geometric primitives from point cloud (surface segmentation and fitting). This paper presents a method for recognition of one class of quadrics from 3D point clouds, in particular for recognition of cylinders, elliptical cylinders and ellipsoids. The method is based on the properties of scatter matrix during direct least squares fitting of ellipsoids. Presented recognition procedure can be employed for segmentation of regions with G1 or higher continuity, and this is its comparative advantage to similar methods. The applicability of the method is illustrated and experimentally verified using two case studies. First case study refers to a synthesized, and the second to a real-world scanned point cloud.",
publisher = "Elsevier B.V.",
journal = "Procedia CIRP - 49th CIRP Conference on Manufacturing Systems (CIRP-CMS 2016)",
title = "Recognition of one class of quadrics from 3D point clouds",
pages = "297-292",
volume = "57",
doi = "10.1016/j.procir.2016.11.051"
}

Jakovljević, Ž., Marković, V., Puzović, R.,& Majstorović, V. D.. (2016). Recognition of one class of quadrics from 3D point clouds. in Procedia CIRP - 49th CIRP Conference on Manufacturing Systems (CIRP-CMS 2016)
Elsevier B.V.., 57, 292-297.
https://doi.org/10.1016/j.procir.2016.11.051

Jakovljević Ž, Marković V, Puzović R, Majstorović VD. Recognition of one class of quadrics from 3D point clouds. in Procedia CIRP - 49th CIRP Conference on Manufacturing Systems (CIRP-CMS 2016). 2016;57:292-297.
doi:10.1016/j.procir.2016.11.051 .

Jakovljević, Živana, Marković, Veljko, Puzović, Radovan, Majstorović, Vidosav D., "Recognition of one class of quadrics from 3D point clouds" in Procedia CIRP - 49th CIRP Conference on Manufacturing Systems (CIRP-CMS 2016), 57 (2016):292-297,
https://doi.org/10.1016/j.procir.2016.11.051 . .

TY  - CONF
AU  - Marković, Veljko
AU  - Jakovljević, Živana
AU  - Miljković, Zoran
PY  - 2016
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/4559
AB  - U radu je predstavljen metod automatskog izbora pragova segmentacije zasnovan na upotrebi veštačkih neuronskih mreža. Ovaj metod predstavlja dopunu algoritmu segmentacije jedne klase kvadrika iz struktuiranih oblaka tačaka čime ga čini visoko autonomnim. Upotreba neuronskih mreža u ovom slučaju je bazirana na njihovom prethodnom obučavanju, a zatim korišćenju za automatsko generisanje pragova pri segmentaciji skeniranih kontura i struktuiranih oblaka tačaka od interesa. Za obučavanje mreža korišćeni su odgovrajući parametri jednog broja G1 kontinualnih sintetizovanih kontura koje sadrže eliptične segmente. Korišćenjem istih uslova obučen je određeni broj mreža različitih struktura koje su iskorišćene za segmentaciju jednog sintetizovanog struktuiranog oblaka tačaka. Izvršena je analiza rezultata segmentacije i
izdvojena je mreža sa najboljim performansama. Njenom upotrebom su zatim automatski generisane vrednosti pragova za segmentaciju i jednog realnog oblaka tačaka čime je izvršena eksperimentalna verifikacija predloženog metoda.
AB  - This paper presents a method for automatic detection of thresholds in segmentation of quadrics
from structured point clouds. The method employs artificial neural networks and it presents an addition to previously developed algorithm for segmentation of a class of quadric surfaces from structured 3D point clouds. Trained neural networks generate thresholds values for segmentation of scanned contours and point clouds. A number of G1 continuous synthesized contours with elliptical segments represent a basis for network training. We have trained several neural networks with different structures under the same conditions. The best available neural network is chosen based on the results of segmentation of one synthesized structured point cloud. We have tested this neural network in estimation of thresholds for segmentation of one real world
point cloud and it has shown excellent performance.
PB  - JUPITER Asocijacija, Univerzitet u Beogradu - Mašinski fakultet
C3  - 40th JUPITER Conference, Proceedings, Beograd, maj 2016.
T1  - Сегментација једне класе површи другог реда из структуираног облака тачака: проблем одређивања прагова
T1  - Segmentation of One Class of Quadric Surfaces from Structured Point Clouds: Thresholds Determination Issue
EP  - 4.17
SP  - 4.7
UR  - https://hdl.handle.net/21.15107/rcub_machinery_4559
ER  - 

@conference{
author = "Marković, Veljko and Jakovljević, Živana and Miljković, Zoran",
year = "2016",
abstract = "U radu je predstavljen metod automatskog izbora pragova segmentacije zasnovan na upotrebi veštačkih neuronskih mreža. Ovaj metod predstavlja dopunu algoritmu segmentacije jedne klase kvadrika iz struktuiranih oblaka tačaka čime ga čini visoko autonomnim. Upotreba neuronskih mreža u ovom slučaju je bazirana na njihovom prethodnom obučavanju, a zatim korišćenju za automatsko generisanje pragova pri segmentaciji skeniranih kontura i struktuiranih oblaka tačaka od interesa. Za obučavanje mreža korišćeni su odgovrajući parametri jednog broja G1 kontinualnih sintetizovanih kontura koje sadrže eliptične segmente. Korišćenjem istih uslova obučen je određeni broj mreža različitih struktura koje su iskorišćene za segmentaciju jednog sintetizovanog struktuiranog oblaka tačaka. Izvršena je analiza rezultata segmentacije i
izdvojena je mreža sa najboljim performansama. Njenom upotrebom su zatim automatski generisane vrednosti pragova za segmentaciju i jednog realnog oblaka tačaka čime je izvršena eksperimentalna verifikacija predloženog metoda., This paper presents a method for automatic detection of thresholds in segmentation of quadrics
from structured point clouds. The method employs artificial neural networks and it presents an addition to previously developed algorithm for segmentation of a class of quadric surfaces from structured 3D point clouds. Trained neural networks generate thresholds values for segmentation of scanned contours and point clouds. A number of G1 continuous synthesized contours with elliptical segments represent a basis for network training. We have trained several neural networks with different structures under the same conditions. The best available neural network is chosen based on the results of segmentation of one synthesized structured point cloud. We have tested this neural network in estimation of thresholds for segmentation of one real world
point cloud and it has shown excellent performance.",
publisher = "JUPITER Asocijacija, Univerzitet u Beogradu - Mašinski fakultet",
journal = "40th JUPITER Conference, Proceedings, Beograd, maj 2016.",
title = "Сегментација једне класе површи другог реда из структуираног облака тачака: проблем одређивања прагова, Segmentation of One Class of Quadric Surfaces from Structured Point Clouds: Thresholds Determination Issue",
pages = "4.17-4.7",
url = "https://hdl.handle.net/21.15107/rcub_machinery_4559"
}

Marković, V., Jakovljević, Ž.,& Miljković, Z.. (2016). Сегментација једне класе површи другог реда из структуираног облака тачака: проблем одређивања прагова. in 40th JUPITER Conference, Proceedings, Beograd, maj 2016.
JUPITER Asocijacija, Univerzitet u Beogradu - Mašinski fakultet., 4.7-4.17.
https://hdl.handle.net/21.15107/rcub_machinery_4559

Marković V, Jakovljević Ž, Miljković Z. Сегментација једне класе површи другог реда из структуираног облака тачака: проблем одређивања прагова. in 40th JUPITER Conference, Proceedings, Beograd, maj 2016.. 2016;:4.7-4.17.
https://hdl.handle.net/21.15107/rcub_machinery_4559 .

Marković, Veljko, Jakovljević, Živana, Miljković, Zoran, "Сегментација једне класе површи другог реда из структуираног облака тачака: проблем одређивања прагова" in 40th JUPITER Conference, Proceedings, Beograd, maj 2016. (2016):4.7-4.17,
https://hdl.handle.net/21.15107/rcub_machinery_4559 .

TY  - CONF
AU  - Jakovljević, Živana
AU  - Marković, Veljko
AU  - Živanović, Saša
PY  - 2015
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/5078
AB  - This paper presents a method for recognition of second order surfaces (quadrics) from point clouds containing information about scanned rotational parts. The method is region growing method that exploits the scatter of data during least squares fitting of quadrics as a region growing criterion. The presented procedure is convenient for segmentation of regions with high (G1 or higher) continuity. Besides, the region seed point is automatically selected which is its comparative advantage to a number of existing methods. The applicability of the proposed method is evaluated using two case studies; the first case study refers to a synthesized signal, and the second presents the applicability of the method on a real world example.
PB  - Faculty of Technical Sciences, Department of Production Engineering
C3  - Proceedings of 12th International Scientific Conference mma 2015 - Advanced Production Technologies
T1  - Recognition of quadrics from 3d point clouds generated by scanning of rotational parts
EP  - 148
SP  - 145
UR  - https://hdl.handle.net/21.15107/rcub_machinery_5078
ER  - 

@conference{
author = "Jakovljević, Živana and Marković, Veljko and Živanović, Saša",
year = "2015",
abstract = "This paper presents a method for recognition of second order surfaces (quadrics) from point clouds containing information about scanned rotational parts. The method is region growing method that exploits the scatter of data during least squares fitting of quadrics as a region growing criterion. The presented procedure is convenient for segmentation of regions with high (G1 or higher) continuity. Besides, the region seed point is automatically selected which is its comparative advantage to a number of existing methods. The applicability of the proposed method is evaluated using two case studies; the first case study refers to a synthesized signal, and the second presents the applicability of the method on a real world example.",
publisher = "Faculty of Technical Sciences, Department of Production Engineering",
journal = "Proceedings of 12th International Scientific Conference mma 2015 - Advanced Production Technologies",
title = "Recognition of quadrics from 3d point clouds generated by scanning of rotational parts",
pages = "148-145",
url = "https://hdl.handle.net/21.15107/rcub_machinery_5078"
}

Jakovljević, Ž., Marković, V.,& Živanović, S.. (2015). Recognition of quadrics from 3d point clouds generated by scanning of rotational parts. in Proceedings of 12th International Scientific Conference mma 2015 - Advanced Production Technologies
Faculty of Technical Sciences, Department of Production Engineering., 145-148.
https://hdl.handle.net/21.15107/rcub_machinery_5078

Jakovljević Ž, Marković V, Živanović S. Recognition of quadrics from 3d point clouds generated by scanning of rotational parts. in Proceedings of 12th International Scientific Conference mma 2015 - Advanced Production Technologies. 2015;:145-148.
https://hdl.handle.net/21.15107/rcub_machinery_5078 .

Jakovljević, Živana, Marković, Veljko, Živanović, Saša, "Recognition of quadrics from 3d point clouds generated by scanning of rotational parts" in Proceedings of 12th International Scientific Conference mma 2015 - Advanced Production Technologies (2015):145-148,
https://hdl.handle.net/21.15107/rcub_machinery_5078 .

TY  - CONF
AU  - Jakovljević, Živana
AU  - Marković, Veljko
PY  - 2015
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/5178
AB  - Critical elements of the state of the art three-dimensional (3D) point cloud processing software are the algorithms for retrieval of high level geometric primitives from raw data. This paper presents a method for recognition of a class of quadric surfaces, in particular for recognition of cylinders, elliptical cylinders, and ellipsoids from 3D point clouds. The method is based on direct least squares fitting of ellipsoids, and it exploits the closeness of scatter matrix to singular in the case when data are sampled for an approximate ellipsoid. This method belongs to the class of region growing methods, and the region is expanded using region growing strategy that is also proposed in this paper. Presented recognition procedure is suitable for segmentation of regions with G1 or higher continuality, and this is its advantage when compared to similar methods. Besides, recognition of quadric surfaces can be performed on unstructured, as well as on structured point clouds. The applicability of the method is illustrated and experimentally verified using two examples that contain G1 continuous surfaces from the considered class. The first example represents synthesized, and the second real-world scanned point cloud.
C3  - International Working Conference “Total Quality Management – Advanced and Intelligent Approaches’’, Proceedings
T1  - Recognition of one class of quadric surfaces from unstructured point cloud
EP  - 360
SP  - 353
UR  - https://hdl.handle.net/21.15107/rcub_machinery_5178
ER  - 

@conference{
author = "Jakovljević, Živana and Marković, Veljko",
year = "2015",
abstract = "Critical elements of the state of the art three-dimensional (3D) point cloud processing software are the algorithms for retrieval of high level geometric primitives from raw data. This paper presents a method for recognition of a class of quadric surfaces, in particular for recognition of cylinders, elliptical cylinders, and ellipsoids from 3D point clouds. The method is based on direct least squares fitting of ellipsoids, and it exploits the closeness of scatter matrix to singular in the case when data are sampled for an approximate ellipsoid. This method belongs to the class of region growing methods, and the region is expanded using region growing strategy that is also proposed in this paper. Presented recognition procedure is suitable for segmentation of regions with G1 or higher continuality, and this is its advantage when compared to similar methods. Besides, recognition of quadric surfaces can be performed on unstructured, as well as on structured point clouds. The applicability of the method is illustrated and experimentally verified using two examples that contain G1 continuous surfaces from the considered class. The first example represents synthesized, and the second real-world scanned point cloud.",
journal = "International Working Conference “Total Quality Management – Advanced and Intelligent Approaches’’, Proceedings",
title = "Recognition of one class of quadric surfaces from unstructured point cloud",
pages = "360-353",
url = "https://hdl.handle.net/21.15107/rcub_machinery_5178"
}

Jakovljević, Ž.,& Marković, V.. (2015). Recognition of one class of quadric surfaces from unstructured point cloud. in International Working Conference “Total Quality Management – Advanced and Intelligent Approaches’’, Proceedings, 353-360.
https://hdl.handle.net/21.15107/rcub_machinery_5178

Jakovljević Ž, Marković V. Recognition of one class of quadric surfaces from unstructured point cloud. in International Working Conference “Total Quality Management – Advanced and Intelligent Approaches’’, Proceedings. 2015;:353-360.
https://hdl.handle.net/21.15107/rcub_machinery_5178 .

Jakovljević, Živana, Marković, Veljko, "Recognition of one class of quadric surfaces from unstructured point cloud" in International Working Conference “Total Quality Management – Advanced and Intelligent Approaches’’, Proceedings (2015):353-360,
https://hdl.handle.net/21.15107/rcub_machinery_5178 .

TY  - CONF
AU  - Marković, Veljko
AU  - Jakovljević, Živana
PY  - 2014
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/5615
AB  - U radu se predlaže metod za segmentaciju jedne klase površi drugog reda (kvadrika) iz struktuiranog oblaka tačaka. Metod je zasnovan na segmentaciji elipsi iz skeniranih linija direktnom regresijom metodom najmanjih kvadrata. Segmentacijom elipsi u oba pravca struktuiranog oblaka mogu se efikasno izdvojiti G1 (i više) kontinualni regioni koji odgovaraju određenim površima drugog reda. Predloženi metod je pre svega namenjen segmentaciji eliptičkih cilindara i elipsoida čije posebne slučajeve predstavljaju cilindar i sfera, a u zavisnosti od načina skeniranja može se upotrebiti i za segmentaciju drugih kvadrika (na primer konusa). Pored toga, u radu se pokazuje da metod daje dobre rezultate i u segmentaciji površi višeg reda u odnosu na kvadrike – na primer eliptičkih torusa. 
Predloženi metod je eksperimentalno verifikovan na većem broju sintetizovanih oblaka tačaka kao i na primeru skeniranog dela iz realnog sveta.
C3  - 39. JUPITER konferencija, Zbornik radova
T1  - Segmentacija jedne klase površi drugog reda iz struktuiranog oblaka tačaka
EP  - 4.22
SP  - 4.13
UR  - https://hdl.handle.net/21.15107/rcub_machinery_5615
ER  - 

@conference{
author = "Marković, Veljko and Jakovljević, Živana",
year = "2014",
abstract = "U radu se predlaže metod za segmentaciju jedne klase površi drugog reda (kvadrika) iz struktuiranog oblaka tačaka. Metod je zasnovan na segmentaciji elipsi iz skeniranih linija direktnom regresijom metodom najmanjih kvadrata. Segmentacijom elipsi u oba pravca struktuiranog oblaka mogu se efikasno izdvojiti G1 (i više) kontinualni regioni koji odgovaraju određenim površima drugog reda. Predloženi metod je pre svega namenjen segmentaciji eliptičkih cilindara i elipsoida čije posebne slučajeve predstavljaju cilindar i sfera, a u zavisnosti od načina skeniranja može se upotrebiti i za segmentaciju drugih kvadrika (na primer konusa). Pored toga, u radu se pokazuje da metod daje dobre rezultate i u segmentaciji površi višeg reda u odnosu na kvadrike – na primer eliptičkih torusa. 
Predloženi metod je eksperimentalno verifikovan na većem broju sintetizovanih oblaka tačaka kao i na primeru skeniranog dela iz realnog sveta.",
journal = "39. JUPITER konferencija, Zbornik radova",
title = "Segmentacija jedne klase površi drugog reda iz struktuiranog oblaka tačaka",
pages = "4.22-4.13",
url = "https://hdl.handle.net/21.15107/rcub_machinery_5615"
}

Marković, V.,& Jakovljević, Ž.. (2014). Segmentacija jedne klase površi drugog reda iz struktuiranog oblaka tačaka. in 39. JUPITER konferencija, Zbornik radova, 4.13-4.22.
https://hdl.handle.net/21.15107/rcub_machinery_5615

Marković V, Jakovljević Ž. Segmentacija jedne klase površi drugog reda iz struktuiranog oblaka tačaka. in 39. JUPITER konferencija, Zbornik radova. 2014;:4.13-4.22.
https://hdl.handle.net/21.15107/rcub_machinery_5615 .

Marković, Veljko, Jakovljević, Živana, "Segmentacija jedne klase površi drugog reda iz struktuiranog oblaka tačaka" in 39. JUPITER konferencija, Zbornik radova (2014):4.13-4.22,
https://hdl.handle.net/21.15107/rcub_machinery_5615 .

TY  - CONF
AU  - Jakovljević, Živana
AU  - Marković, Veljko
AU  - Miladinović, Momčilo
PY  - 2014
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/5617
AB  - Cylindrical surfaces, as one of the most frequent surfaces in mechanical engineering, are represented by elliptical (circular) or linear segments in scanned lines within structured point cloud. Having this in mind, segmentation and fitting of elliptical regions is a very important issue in the recognition of cylindrical surfaces. This paper presents the research in the recognition of elliptical (or circular) segments in scanned lines. Segments connected with G1 (or higher) continuity are considered. Presented method is based on seed independent region growing using direct least squares fitting of ellipses. The method is tested in the case studies considering synthesized as well as real world (scanned lines) examples.
C3  - ETIKUM 2014, Zbornik radova
T1  - Recognition of elliptical segments in scanned lines
EP  - 22
SP  - 19
UR  - https://hdl.handle.net/21.15107/rcub_machinery_5617
ER  - 

@conference{
author = "Jakovljević, Živana and Marković, Veljko and Miladinović, Momčilo",
year = "2014",
abstract = "Cylindrical surfaces, as one of the most frequent surfaces in mechanical engineering, are represented by elliptical (circular) or linear segments in scanned lines within structured point cloud. Having this in mind, segmentation and fitting of elliptical regions is a very important issue in the recognition of cylindrical surfaces. This paper presents the research in the recognition of elliptical (or circular) segments in scanned lines. Segments connected with G1 (or higher) continuity are considered. Presented method is based on seed independent region growing using direct least squares fitting of ellipses. The method is tested in the case studies considering synthesized as well as real world (scanned lines) examples.",
journal = "ETIKUM 2014, Zbornik radova",
title = "Recognition of elliptical segments in scanned lines",
pages = "22-19",
url = "https://hdl.handle.net/21.15107/rcub_machinery_5617"
}

Jakovljević, Ž., Marković, V.,& Miladinović, M.. (2014). Recognition of elliptical segments in scanned lines. in ETIKUM 2014, Zbornik radova, 19-22.
https://hdl.handle.net/21.15107/rcub_machinery_5617

Jakovljević Ž, Marković V, Miladinović M. Recognition of elliptical segments in scanned lines. in ETIKUM 2014, Zbornik radova. 2014;:19-22.
https://hdl.handle.net/21.15107/rcub_machinery_5617 .

Jakovljević, Živana, Marković, Veljko, Miladinović, Momčilo, "Recognition of elliptical segments in scanned lines" in ETIKUM 2014, Zbornik radova (2014):19-22,
https://hdl.handle.net/21.15107/rcub_machinery_5617 .