The evaluation of the proposed approach on our surveillance dataset shows that our approach is very effective for determining the classes of moving objects in a moving camera setting.
📌 3 Key Takeaways
🎯
Objective & Hypothesis:Öz In this paper, we present a novel method to detect and classify moving objects from surveillance videos that are obtained from a moving camera.
📊
Key Findings & Data:Considering these regions as priors, we apply an efficient segmentation algorithm to obtain accurate object boundaries for the moving objects.
💡
Conclusion & Impact:The evaluation of the proposed approach on our surveillance dataset shows that our approach is very effective for determining the classes of moving objects in a moving camera setting.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Anahtar Kelimeler Moving object detection · classification · moving camera
Özet
Öz In this paper, we present a novel method to detect and classify moving objects from surveillance videos that are obtained from a moving camera. In our method, we first estimate the camera motion by interpreting the movement of interest points in the scene. Then, we eliminate the camera motion and find candidate regions that belong to the moving objects. Considering these regions as priors, we apply an efficient segmentation algorithm to obtain accurate object boundaries for the moving objects. Finally, we classify the detected objects as people, vehicle, or others using some morphological features and the velocity vectors of moving objects. The evaluation of the proposed approach on our surveillance dataset shows that our approach is very effective for determining the classes of moving objects in a moving camera setting.
SİNCAN, O. M., KELES, H. Y., TOSUN, S. (2018). MOVING OBJECT DETECTION AND CLASSIFICATION IN SURVEILLANCE SYSTEMS USING MOVING CAMERAS. Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering, Cilt: 60 - Sayı: 2, 63–82. https://ajindex.com/articles/51157
P. Remagnino, S. A. Velastin, G. L. Foresti, and M. Trivedi, Novel concepts and challenges for the next generation of video surveillance systems, Machine Vision and Applications, 18/3 (2007) 135-137.
R. Vezzani and R. Cucchiara, Video surveillance online repository (visor): an integrated framework, Multimedia Tools and Applications, 50/2 (2010) 359-380.
K. A. Joshi and D. G. Thakore, A survey on moving object detection and tracking in video surveillance system, International Journal of Soft Computing and Engineering, 2/3 (2012) 44-48.
M. Chate, S. Amudha, V. Gohokar, Object detection and tracking in video sequences, ACEEE International Journal on signal & Image processing, 3/1 (2012).
W.-C. Hu, C.-H. Chen, T.-Y. Chen, D.-Y. Huang, and Z.-C. Wu, Moving object detection and tracking from video captured by moving camera, Journal of Visual Communication and Image Representation, 30 (2015) 164-180.
S. W. Kim, K. Yun, K. M. Yi, S. J. Kim, and J. Y. Choi, Detection of moving objects with a moving camera using non-panoramic background model. Machine Vision and Applications, 24/5 (2013) 1015-1028.
N. Thakoor, J. Gao, and H. Chen, Automatic object detection in video sequences with camera in, In Proceedings of Advanced Concepts for Intelligent Vision Systems, Citeseer, 2004.
Y. Wu, X. He, and T. Q. Nguyen, Moving object detection with a freely moving camera via background motion subtraction, IEEE Transactions on Circuits and Systems for Video Technology, 27/2 (2017) 236-248.
K. Yun, J. Lim, and J. Y. Choi, Scene conditional background update for moving object detection in a moving camera, Pattern Recognition Letters, 88 (2017) 57-63.
O. M. Sincan, V. B. Ajabshir, H. Y. Keles, and S. Tosun. Moving object detection by a mounted moving camera, EUROCON 2015 - International Conference on Computer as a Tool (EUROCON), IEEE, Sept 2015.
L. Bo and Z. Heqin, Using object classification to improve urban traffic monitoring system, In International Conference on Neural Networks and Signal Processing, 2 (2003) 1155-1159.
L. Chen, R. Feris, Y. Zhai, L. Brown, and A. Hampapur, An integrated system for moving object classification in surveillance videos, In 2008 IEEE Fifth International Conference on Advanced Video and Signal Based Surveillance, (2008) 52-59.
M. Elhoseiny, A. Bakry, and A. Elgammal, Multiclass object classification in video surveillance systems-experimental study, In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, (2013) 788-7