Abstract
We propose a novel method for automatic detection of Object of Interest (OOI) and tracking from actively acquired videos. The proposed approach benefits the object-centered property of Active Video and facilitates self-initialization in tracking by a non-calibrated camera. We first use a color-saliency weighted Probability-of-Boundary (cPoB) map for keypoints filtering and salient region detection. Successive Classification Maximum Similarities (SCMS) feature matching is used for tracking between two consecutive frames. A strong classifier trained on-the-fly by AdaBoost is utilized for keypoint classification and subsequent Linear Programming rejects outliers. Experiments demonstrate the importance of active video during the data collection phase and confirm that our new approach can automatically detect and reliably track OOI in videos.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Avidan, S.: Ensemble tracking. In: Proc. Comput. Vision and Pattern Recogn., pp. 494–501 (2005)
Stauffer, C., Eric, W., Grimson, W.E.L.: Learning patterns of activity using real-time tracking. IEEE Trans. Pattern Anal. Mach. Intell. 22, 747–757 (2000)
Kim, Z.: Real time object tracking based on dynamic feature grouping with background subtraction. In: Proc. Comput. Vision and Pattern Recogn., pp. 1–8 (2008)
Yin, Z., Collins, R.T.: Object tracking and detection after occlusion via numerical hybird local and global mode-seeking. In: Proc. Comput. Vision and Pattern Recogn., pp. 1–8 (2008)
Liu, D., Hua, G., Chen, T.: Videocut: Removing irrelevant frames by discovering the object of interest. In: Proc. Europ. Conf. Comput. Vision, pp. I: 441–453 (2008)
Simakov, D., Caspi, Y., Shechtman, E., Irani, M.: Summarizing visual data using bidirectional similarity. In: Proc. Comput. Vision and Pattern Recogn., pp. 1–8 (2008)
Bay, H., Tuytelaars, T., Gool, L.V.: Surf: Speeded up robust features. In: Proc. Europ. Conf. Comput. Vision, pp. 404–417 (2006)
Freund, Y., Schapire, R.E.: A decision-theoretic generalization of on-line learning and an application to boosting. Journal of Computer and System Sciences 55(1), 119–139 (1997)
Lu, Y., Li, Z.N.: Automatic object extraction and reconstruction in active video. Pattern Recogn. 41(3), 1159–1172 (2008)
Itti, L., Koch, C., Niebur, E.: A model of saliency-based visual attention for rapid scene analysis. IEEE Trans. Pattern Anal. Mach. Intell. 20(11), 1254–1259 (1998)
Hu, Y., Xie, X., Ma, W.Y., Chia, L.T., Rajan, D.: Salient region detection using weighted feature maps based on the human visual attention model. In: Proc. IEEE Pacific-Rim Conference on Multimedia (2004)
You, W., Jiang, H., Li, Z.N.: Real-time multiple object tracking in smart environments. In: Proc. Int’l. Conf. on Robotics and Biomimetics, pp. 818–823 (2008)
Collins, R.T., Liu, Y.: On-line selection of discriminative tracking features. In: Proc. Int’l. Conf. Comput. Vision, pp. 346–352 (2003)
Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int’l. J. of Comp. Vision 60, 91–110 (2004)
Huang, J., Li, Z.N.: Image trimming via saliency region detection and iterative feature matching. In: Proc. Int’l. Conf. on Multimedia Expo. (2009)
Martin, D.R., Fowlkes, C.C., Malik, J.: Learning to detect natural image boundaries using local brightness, color, and texture cues. IEEE Trans. Pattern Anal. Mach. Intell. 26(5), 530–549 (2004)
Sizintsev, M., Derpanis, K.G., Hogue, A.: Histogram-based search: A comparative study. In: Proc. Comput. Vision and Pattern Recogn., pp. 1–8 (2008)
Mahadevan, V., Vasconcelos, N.: Background subtraction in highly dynamic scenes. In: Proc. Comput. Vision and Pattern Recogn., pp. 1–8 (2008)
Rubner, Y., Tomasi, C., Guibas, L.J.: The earth mover’s distance as a metric for image retrieval. Int’l. J. of Comp. Vision 40(2), 99–121 (2000)
Barber, C.B., Dobkin, D.P., Huhdanpaa, H.: The quickhull algorithm for convex hulls. ACM Transactions on Mathematical Software 22, 469–483 (1995)
Comaniciu, D., Ramesh, V., Meer, P.: Kernel-based object tracking. IEEE Trans. Pattern Anal. Mach. Intell. 25, 564–577 (2003)
Ghanbari, M.: Video Coding: An Introduction to Standard Codecs. Institution of Electrical Engineers, Stevenage (1999)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Huang, J., Li, ZN. (2009). Automatic Detection of Object of Interest and Tracking in Active Video. In: Muneesawang, P., Wu, F., Kumazawa, I., Roeksabutr, A., Liao, M., Tang, X. (eds) Advances in Multimedia Information Processing - PCM 2009. PCM 2009. Lecture Notes in Computer Science, vol 5879. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10467-1_32
Download citation
DOI: https://doi.org/10.1007/978-3-642-10467-1_32
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-10466-4
Online ISBN: 978-3-642-10467-1
eBook Packages: Computer ScienceComputer Science (R0)