Abstract
Local appearance of object is of importance to content analysis, object recognition and forensic authentication. However, existing video surveillance systems are almost incapable of capturing local appearance of object in a remote scene. We present a video surveillance system in dealing with object tracking and local appearance capturing in a remote scene, which consists of one pan&tilt and two cameras with different focuses. One camera has short focus lens for object tracking while the other has long ones for local appearance capturing. Video object can be located via just one manual selection or motion detection, which is switched into a modified kernel-based tracking algorithm absorbing both color value and gradient distribution. Meanwhile, local appearance of object such as face is captured via long focus camera. Both simulated and real-time experiments of the proposed system have achieved promising results.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
References
Foresti, G.L.: Object Recognition and Tracking for Remote Video Surveillance. IEEE Transactions on Circuits and Systems for Video Technology 9, 1045–1062 (1999)
Bue, A.D., Comaniciu, D., Ramesh, V., Regazzoni, C.: Smart cameras with real-time video object generation. In: Proceedings of International Conference on Image Processing, pp. 429–432 (2002)
Chen, T.-W., Hsu, S.-C., Chien, S.-Y.: Automatic Feature-based Face Scoring in Surveillance Systems. In: IEEE International Symposium on Multimedia, pp. 139–146 (2007)
Liang, D., Huang, Q., Jiang, S., et al.: Mean-shift Blob Tracking with Adaptive Feature Selection and Scale Adaptation. In: IEEE International Conference on Image Processing, San Antonio, United States, pp. 369–372 (2007)
Chang, C., Ansari, R., Khokhar, A.: Multiple Object Tracking with Kernel Particle Filter. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Diego, vol. 1, pp. 566–573 (2005)
Shiu, Y., Kuo, C.-C.J.: A Modified Kalman Filtering Approach to On-Line Musical Beat Tracking. In: IEEE International Conference on Acoustics, Speech and Signal Processing, vol. 2, pp. 765–768 (2007)
Lee, S.-W., Kang, J., Shin, J., et al.: Hierarchical Active Shape Model with Motion Prediction for Real-time Tracking of Non-rigid Objects. IET Comput. Vis. 1(1), 17–24 (2007)
Comaniciu, D., Meer, P.: Mean Shift: A Robust Approach Toward Feature Space Analysis. IEEE Transaction on Pattern Analysis and machine Intelligence 24(5), 603–619 (2002)
Comaniciu, D., Ramesh, V., Meer, P.: Kernel-based Object Tracking. IEEE Transaction on Pattern Analysis and machine Intelligence 25(5), 564–577 (2003)
Yang, C., Duraiswami, R., Davis, L.: Efficient Mean-Shift Tracking via a New Similarity Measure. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Diego, vol. 1, pp. 176–183 (2005)
Collins, R.T., Liu, Y., Leordeanu, M.: Online selection of discriminative tracking features. IEEE Transaction on Pattern Analysis and Machine Intelligence 27(10), 1631–1643 (2005)
Perez, P., Hue, C., Vermaak, J., Gangnet, M.: Color-Based Probabilistic Tracking. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002. LNCS, vol. 2350, pp. 661–675. Springer, Heidelberg (2002)
Maggio, E., Cavallaro, A.: Multi-Part Target Representation for Color Tracking. In: Proceedings of International Conference on Image Processing, pp. 729–732 (2005)
Salembier, P., Oliveras, A., Garrido, L.: Antiextensive Connected Operators for Image and Sequence Processing. IEEE Transactions on Image Processing 7, 555–570 (1998)
Jones, M., Viola, P.: Rapid Object Detection using a Boosted Cascade of Simple Features. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 511–518 (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Yang, W., Zhou, F., Liao, Q. (2010). Object Tracking and Local Appearance Capturing in a Remote Scene Video Surveillance System with Two Cameras. In: Boll, S., Tian, Q., Zhang, L., Zhang, Z., Chen, YP.P. (eds) Advances in Multimedia Modeling. MMM 2010. Lecture Notes in Computer Science, vol 5916. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11301-7_49
Download citation
DOI: https://doi.org/10.1007/978-3-642-11301-7_49
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-11300-0
Online ISBN: 978-3-642-11301-7
eBook Packages: Computer ScienceComputer Science (R0)