3D objects modelling and description from a traffic flow

• Autorzy: Bojmir M. , Hudec R. , Kamencay P. , Pirnik R.
• Języki publikacji: EN

Abstrakty

EN

Contemporary research activities in the area of transportation systems usually utilize computer vision techniques. These activities are mostly oriented to the analysis of traffic flow. Key parts of the analysis consist of detection, extraction, modelling and recognition of objects in the traffic flow. Additional information can be obtained by the object tracking, too. The main aim of this contribution is to propose a new method for modelling 3D objects that are moving in the traffic flow. At the beginning of this paper, basic methods of object detection and extraction are shortly described. Moreover, the modified algorithm based on the object extraction and 3D models creation by mesh is also proposed. That mesh model is generated from a depth map. Finally, the results of proposed method are presented in the last part of this paper.

Słowa kluczowe

EN

vehicle detection; vehicle extraction; depth map; 3D modelling polygonal mesh

PL

detekcja pojazdów; ekstrakcja pojazdów; mapa głębi; modelowanie 3D

• Wydawca: Polskie Stowarzyszenie Telematyki Transportu
• Czasopismo: Archives of Transport System Telematics
• Rocznik: 2013
• Tom: Vol. 6, iss. 3
• Strony: 4--9
• Opis fizyczny: Bibliogr. 8 poz.

Twórcy

autor

Bojmir M.

• Univeristy of Zilina, Faculty of Electrical Engineering, Department of Telecommunications and Multimedia, Univerzitna 8215/1 010 26 Zilina, Slovakia

autor

Hudec R.

• Univeristy of Zilina, Faculty of Electrical Engineering, Department of Telecommunications and Multimedia, Univerzitna 8215/1 010 26 Zilina, Slovakia

autor

Kamencay P.

• Univeristy of Zilina, Faculty of Electrical Engineering, Department of Telecommunications and Multimedia, Univerzitna 8215/1 010 26 Zilina, Slovakia

autor

Pirnik R.

• Univeristy of Zilina, Faculty of Electrical Engineering, Department of Control and Information Systems, Univerzitna 8215/1 010 26 Zilina, Slovakia

Bibliografia

• [1] Directorate-General for Research, European Union: Intelligent transport systems, http://www.greendigitalcharter.eu/wpcontent/uploads/2012/11/2010-European-Commission-Report-on-Intelligent-Transport-Systems.pdf, 2010
• [2] Kamath , A.: Image Processing and Particle Analysis for Road Traffic Detection, International Journal of Computer Applications (0975–8887) Volume 55–No.2, October 2012, http://research.ijcaonline.org/volume55/number2/pxc3882604.pdf
• [3] Ghosh , N.: Unsupervised Learning for Incremental 3-D Modeling, IEEE Transactions on intelligent transportation systems, vol 11, no. 2, 2010 http://vislab.ucr.edu/RESEARCH/sample_research/AAAIworkshop’05 final paper.pdf
• [4] Wojek , Ch.: Monocular 3D Scene Modeling and Inference: Understanding Multi-Object Traffic Scenes, Lecture Notes in Computer Science Volume 6314, 467-481, 2010
• [5] Kamencay , P.: Improved Depth Map Estimation from Stereo Images Based on Hybrid Method, Radioengineering 2012/4, Volume 21, Issue 1, Pages: 70-78, Part 1, http://www.radioeng.cz/fulltexts/2012/ 12_01_0070_ 0078.pdf
• [6] Navab , N., Unger , Ch.: Stereo Vision II: Dense Stereo Matching, 2011 http://campar.in.tum.de/twiki/pub/Chair/TeachingWs11Cv2/3D_CV2_WS_2011_Stereo.pdf
• [7] Bay , H., Ess, A., Tuytelaars , T., Van Gool , L.: Speeded-up robust features (surf) Computer Vision and Image Understanding 110, 2008, 346–359
• [8] Knopp , J., Prasad , M.: Hough Transforms and 3D SURF for robust three dimensional classication, Lecture Notes in Computer Science Volume 6316, Pages 589-602, 2010, http://link.springer.com/content/pdf/10.1007%2F978-3-642-15567-3_43.pdf