Abstract
This chapter describes a moving object detection-and-localization method based on forward-backward motion history images (MHIs). Detecting moving objects automatically is a key component of an automatic visual surveillance and tracking system. In airborne thermal video especially, the moving objects may be small, color information is not available, and intensity appearance may be camouflaged. Although it is challenging for an appearance-or shape-based detector to detect the small objects in thermal images, pixel-level change detection or optical flow can provide powerful motion-based cues for detecting and localizing the objects. Previous motion detection approaches often use background subtraction, interframe difference, or three-frame difference, which are either costly or can only partially detect the object. We propose an MHI-based method that can accurately detect location and shape of moving objects for initializing a tracker or recovering from tracking failure. The effectiveness of this method is quantified using long and varied video sequences.
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Chapter's References
S. Ali and M. Shah, COCOA—Tracking in Aerial Imagery, demo at ICCV 2005, Beijing China, October 15–21
A. Bobick and J. Davis, The Recognition of Human Movement Using Temporal Templates, IEEE Transactions on Pattern Analysis and Machine Intelligence, 23(3):257–267, March 2001
G. Bradski and J. Davis. Motion segmentation and pose recognition with motion history gradients, Fifth IEEE Workshop on Application of Computer Vision, 238–244, December 2000
G. Halevi and D. Weinshall. Motion of disturbances: Detection and tracking of multi-body non-rigid motion, IEEE Conference on Computer Vision and Pattern Recognition, Puerto Rico, 1997, pp. 897–902
I. Haritaoglu, D. Harwood, and L. Davis. W4: Real-time surveillance of people and their activities, IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(8):809–830, August 2000
IEEE OTCBVS WS Series Bench; J. Davis and V. Sharma, Fusion-based background-subtraction using contour saliency, in Proceedings of IEEE International Workshop on Object Tracking and Classification Beyond the Visible Spectrum, June 2005
IEEE OTCBVS WS Series Bench; R. Miezianko, Terravic Research Infrared Database. http://www.cse.ohio-state.edu/otcbvs-bench/
M. Irani and P. Anandan. A unified approach to moving object detection in 2D and 3D scenes, IEEE Transactions on Pattern Analysis and Machine Intelligence, 20(6):577–589, June 1998
R. Kumar, H. Sawhney, et.al, Aerial video surveillance and exploitation, Proceedings of the IEEE, 89(10):1518–1539, October 2001
N. Paragios and R. Deriche. Geodesic active contours and level sets for the detection and tracking of moving objects, IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(3):266–280, March 2000
C. Stauffer and W. Grimson. Learning patterns of activity using real-time tracking, IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(8):747–757, August 2000
A. Strehl and J. Aggarwal. Detecting moving objects in airborne forward looking infrared sequences, Proceedings of the IEEE Workshop on Computer Vision Beyond the Visible Spectrum: Methods and Applications IEEE Computer Society, Washington, DC, USA, 1999, ISBN:0-7695-0050-1
L. Wixson. Detecting salient motion by accumulating directionally-consistent flow, IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(8):774–780, August 2000
H. Yalcin, R. Collins, and M. Hebert. Background estimation under rapid gain change in thermal imagery, Second IEEE Workshop on Object Tracking and Classification in and Beyond the Visible Spectrum, June 20–26, 2005
Z. Yin and R. Collins. Moving object localization in thermal imagery by forward-backward MHI, Third IEEE Workshop on Object Tracking and Classification in and Beyond the Visible Spectrum, New York City, June 2006
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Yin, Z., Collins, R. (2009). Moving Object Localization in Thermal Imagery by Forward-Backward Motion History Images. In: Hammoud, R.I. (eds) Augmented Vision Perception in Infrared. Advances in Pattern Recognition. Springer, London. https://doi.org/10.1007/978-1-84800-277-7_12
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DOI: https://doi.org/10.1007/978-1-84800-277-7_12
Publisher Name: Springer, London
Print ISBN: 978-1-84800-276-0
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