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Images constitute data that lives in a very high dimensional space, typically of the order of hundred thousand dimensions. Drawing inferences from data of such high dimensions soon becomes intractable. Therefore traditionally several of these problems like face recognition, object recognition, scene understanding etc. have been approached using techniques in pattern recognition. Such methods in conjunction with methods for dimensionality reduction have been highly popular and successful in tackling several image processing tasks. Of late, the advent of cheap, high quality video cameras has generated new interests in extending still image-based recognition methodologies to video sequences. The added temporal dimension in these videos makes problems like face and gait-based human recognition, event detection, activity recognition addressable. Our research has focussed on solving several of these problems through a pattern recognition approach. Of course, in video streams patterns refer to both patterns in the spatial structure of image intensities around interest points and temporal patterns that arise either due to camera motion or object motion. In this paper, we discuss the applications of pattern recognition in video to problems like tracking, face and gait-based human recognition, activity recognition and activity based person identification. Rama Chellappa, Ashok Veeraraghavan and Gaurav Aggarwal. "Pattern Recognition in Video". Invited paper in International Conference on Pattern Recognition and Machine Intelligence(PReMI), 2005. Published in Lecture Notes in Computer Science, Volume 3776, Dec 2005, Pages 11-20 [pdf] |
The fractional Fourier transform: theory, implementation and error analysis
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The fractional Fourier transform is a time-frequency distribution and an extension of the classical Fourier transform. There are several known applications of the fractional Fourier transform in the areas of signal processing, especially in signal restoration and noise removal. This paper provides an introduction to the fractional Fourier transform and its applications. These applications demand the implementation of the discrete fractional Fourier transform on a digital signal processor (DSP). The details of the implementation of the discrete fractional Fourier transform on ADSP-2192 are provided. The effect of finite register length on implementation of discrete fractional Fourier transform matrix is discussed in some detail. This is followed by the details of the implementation and a theoretical model for the fixed-point errors involved in the implementation of this algorithm. It is hoped that this implementation and fixed-point error analysis will lead to a better understanding of the issues involved in finite register length implementation of the discrete fractional Fourier transform and will help the signal processing community make better use of the transform. V.Ashok Narayanan and K.M.M.Prabhu. The fractional Fourier transform: theory, implementation and error analysis. Elsevier Journal on Microprocessors and Microsystems,Volume 27, Issue 10, 3 Nov 2003, Pages 511-521. [pdf] |