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Moving Object Detection and Compression in IR Sequences

Summary: Chapter 5
Moving Object Detection and Compression in
IR Sequences
Namrata Vaswani, Amit K Agrawal, Qinfen Zheng, and Rama Chellappa
Center for Automation Research, University of Maryland, College Park, MD
Summary. We consider the problem of remote surveillance using infrared (IR)
sensors. The aim is to use IR image sequences to detect moving objects (humans
or vehicles), and to transmit a few "best view images" of every new object that is
detected. Since the available bandwidth is usually low, if the object chip is big, it
needs to be compressed before being transmitted. Due to low computational power of
computing devices attached to the sensor, the algorithms should be computationally
simple. We present two approaches for object detection - one which specifically solves
the more difficult long range object detection problem and the other for objects at
short range. For objects at short range, we also present techniques for selecting a
single best view object chip and computationally simple techniques for compressing
it to very low bit rates due to the channel bandwidth constraint. A fast image
chip compression scheme implemented in the wavelet domain by combining a non-
iterative zerotree coding method with 2D-DPCM for both low and high frequency
subbands is presented. Comparisons with some existing schemes are also included.


Source: Agrawal, Amit - Mitsubishi Electric Research Labs
Vaswani, Namrata - Department of Electrical and Computer Engineering, Iowa State University


Collections: Engineering