Abstract
Surveillance of a scene with computer vision faces the challenge of meeting two competing design objectives simultaneously: maintain a sufficient field-of-view coverage and provide adequate details of a target object if and when it appears in the scene. In this paper we propose a dual-camera system for tracking small objects based on a stationary camera and a pantilt- zoom (PTZ) camera. The utilization of two cameras enables us to detect a small object with the stationary camera while tracking it with the second moving camera. We present a method for modeling the dual-camera system and demonstrate how the model can be used in object detection and tracking applications. The main contribution of this paper is that we provide a model for explicitly computing the extrinsic parameters of the PTZ camera with respect to the stationary camera in order to target the moving camera at an object that has been detected by the stationary camera. Our mathematical model combines stereo calibration and hand-eye calibration algorithms as well as the kinematics of the pan-tilt unit, in order for the two cameras to collaborate. We present experimental results of our model in indoor and outdoor applications. The results prove that our dual camera system is an effective solution to the problem of detecting and tracking a small object with both excellent scene coverage and object details.
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References
Bodor, R., Morlok, R., Papanikolopoulos, N.: Dual-camera system for multi-level activity recognition. Intelligent Robots and Systems (IROS) 1, 643–648 (2004)
Cai, Y., Medioni, G.: Towards a practical PTZ face detection and tracking system. In: IEEE Workshop on Applications of Computer Vision (WACV), USA, pp. 31–38 (2013)
Choi, H.C., Park, U., Jain, A.K.: PTZ camera assisted face acquisition, tracking and recognition. In: Fourth IEEE International Conference on Biometrics: Theory Applications and Systems (BTAS), Washington DC (2010)
Detesan, O., Arghir, M., Solea, G.: The Mathematical Model of the Pan-Tilt Unit Used in Noise Measurements in Urban Traffic. In: Fitt, A.D., Norbury, J., Ockendon, H., Wilson, E. (eds.) Progress in Industrial Mathematics at ECMI 2008. Mathematics in Industry, pp. 791–796. Springer, Heidelberg (2010)
Dinh, T., Vo, N., Medioni, G.: High resolution face sequences from a PTZ network camera. In: IEEE International Conference on Automatic Face and Gesture Recognition and Workshops, USA (2011), doi:10.1109/FG.2011.5771454
Dinh, T., Yu, Q., Medioni, G.: Real time tracking using an active pan-tilt-zoom network camera. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), USA (2009), doi:10.1109/IROS.2009.5353915
Hampapur, A., et al.: Face cataloger: Multi-scale imaging for relating identity to location. In: Advanced Video and Signal Based Surveillance (2003)
Lalonde, M., et al.: A system to automatically track humans and vehicles with a PTZ camera. In: Defense and Security Symposium. International Society for Optics and Photonics (2007)
Marchesotti, L., et al.: Cooperative multi-sensor system for real-time face detection and tracking in uncontrolled conditions. In: Image and Video Communications and Processing, pp. 100–114 (2005)
Ngan, P., Valkenburg, R.: Calibrating a pan-tilt camera head. In: Image and Vision Computing Workshop (1995)
Park, F., Bryan, J.: Robot sensor calibration: solving AX=XB on the Euclidean group. IEEE Transactions on Robotics and Automation 10(5), 717–721 (1994)
Paul, R., Zhang, H.: Computationally efficient kinematics for manipulators with spherical wrists. Int. J. Robot. Res. 5(2), 32–44 (1986)
Shiu, Y., Ahmad, S.: Calibration of wrist-mounted robotic sensors by solving homogeneous transform equations of the form AX= XB. IEEE Transactions on Robotics and Automation 5(1), 16–29 (1989)
Stillman, S., Tanawongsuwan, R., Essa, I.: Tracking multiple people with multiple cameras. In: Proc. Int. Conf. Audio and Video based Biometric Person Authentication (1999)
Wang, T., et al.: Active stereo vision for improving long range hearing using a laser Doppler vibrometer. In: IEEE Workshop on Applications of Computer Vision, WACV (2011)
Xu, Y., Song, D.: Systems and algorithms for autonomously simultaneous observation of multiple objects using robotic PTZ cameras assisted by a wide-angle camera. In: IROS, pp. 3802–3807 (2009)
Zhou, F., et al.: A Remote Scene Binocular Video Surveillance System with Small Object Tracking. In: 2nd International Congress on IEEE Image and Signal Processing, CISP 2009 (2009)
Zhou, X., et al.: A Master-Slave System to Acquire Biometric Imagery of Humans at a Distance. In: Proc. ACM SIGGM Intl Workshop Video Surveillance, pp. 113–120 (2003)
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Shakeri, M., Zhang, H. (2015). Cooperative Targeting: Detection and Tracking of Small Objects with a Dual Camera System. In: Mejias, L., Corke, P., Roberts, J. (eds) Field and Service Robotics. Springer Tracts in Advanced Robotics, vol 105. Springer, Cham. https://doi.org/10.1007/978-3-319-07488-7_24
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DOI: https://doi.org/10.1007/978-3-319-07488-7_24
Publisher Name: Springer, Cham
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