Abstract
This paper deals with an intelligent video surveillance system using object tracking and recognition techniques. The proposed system integrates the object extraction, human recognition, face detection, object tracking, and camera control. First, the object in the video frame is extracted using the background subtraction. Then, the object region is examined whether it is human or not. For this recognition, the region-based shape descriptor, angular radial transform, is used to model the human shapes. When the object is decided as human, the face detection is optionally performed to capture the clear face images. Finally, the face or object region is tracked in the video frames, and the pan/tilt/zoom (PTZ) controllable camera also tracks the moving object. The tracking filter updates the histogram information in the object region at every frame so that the moving object is well tracked even though the poses and sizes of object are varied. Since the PTZ parameters can be transformed into camera parameters such as rotation angles and focal length, we estimate the 3-D locations of moving object with multiple PTZ camera. This paper constructs test system with multiple PTZ cameras and their communication protocol. According to the experiments, the proposed system is able to track the moving person automatically not only in the image domain but also in the real 3-D space. The proposed system improves the surveillance efficiency using the usual PTZ cameras.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Valera, M., Velastin, S.: Intelligent distributed surveillance systems: A review. IEEE Proc. Vis. Image, Signal Process. 152(2), 192–204 (2005)
Hampapur, A., et al.: Smart video surveillance: Exploring the concept of multiscale spatiotemporal tracking. IEEE Sig. Proc. Mag. 22(2), 38–51 (2005)
Micheloni, C., Rinner, B., Foresti, G.L.: Video analysis in pan-tilt-zoom camera networks. IEEE Sig. Proc. Mag, 78–90 (September 2010)
Piccardi, M.: Background subtraction techniques: a review. In: IEEE International Conf. on Systems, Man and Cybernetics, pp. 3099–3104 (2004)
Seki, M., Wada, T., Fujiwara, H., Sumi, K.: Background subtraction based on cooccurrence of image variations. In: Proc. of CVPR 2003, vol. 2, pp. 65–72 (2003)
Qureshi, F.Z., Terzopoulos, D.: Planning ahead for PTZ camera assignment and handoff. In: Proc. ACM/IEEE Conf. Distributed Smart Cameras, pp. 1–8 (2009)
Rinner, B., Wolf, W.: Introduction to distributed smart cameras. Proc. IEEE 96(10), 1565–1575 (2008)
Soto, C., Song, B., Roy-Chowdhury, A.: Distributed multi-target tracking in a self-configuring camera network. In: Proc. IEEE CVPR, pp. 1486–1493 (2009)
Yu, D., Hu, J., Yan, H.: A multiple point boundary smoothing algorithm. Pattern Recognition Letters, 657–668 (June 1998)
Jeannin, S.: MPEG-7 visual part of experimentation model version 9.0, in ISO/IEC JTC1/SC29/WG11/N3914 (January 2001)
Coeurjolly, D., Ricard, J., Baskurt, A.: Generalizations of angular radial transform for 2D and 3D shape retrieval. Pattern Recognition Letters 26(14), 2174–2186 (2005)
Yang, M.-H., Kriegman, D.J., Ahuja, N.: Detecting faces in images: A survey. IEEE Trans. on PAMI 24(1), 34–58 (2002)
Hsu, R.-L., Mohamed, A.-M., Jain, A.K.: Face detection in color images. IEEE Trans. on PAMI 24, 696–706 (2002)
Comaniciu, D., Meer, P.: Mean shift: A robust approach toward feature space analysis. IEEE Trans. on PAMI 24(5), 603–619 (2002)
PELCO-D Protocol manual
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Lee, S.H., Sharma, S., Sang, L., Park, JI., Park, Y.G. (2011). An Intelligent Video Security System Using Object Tracking and Shape Recognition. In: Blanc-Talon, J., Kleihorst, R., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2011. Lecture Notes in Computer Science, vol 6915. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23687-7_43
Download citation
DOI: https://doi.org/10.1007/978-3-642-23687-7_43
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23686-0
Online ISBN: 978-3-642-23687-7
eBook Packages: Computer ScienceComputer Science (R0)