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16 April 2008 Feature-aided tracking in the urban environment
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Abstract
The various asymmetrical threats in the urban environment have driven the need for persistent surveillance and methods to exploit the data provided by passive sensing platforms. The primary goal is to track vehicles as they move through the urban environment. The rather large number of ambiguous tracking events requires incorporation of target features to maintain track purity. This paper will discuss a feature extraction technique that will be referred to as "feature-aided" tracking to mitigate some of the tracking issues in this environment (e.g. rotation and illumination invariance, partial occlusion, and move-stop-move transitions). The feature extraction method applied is loosely based on the SPIN histogram method of applying a two-dimensional histogram relative to the center of an object. This paper focuses on applying a simplified version of the intensity-based two-dimensional histogram and gradient-based two-dimensional histogram introduced by the works of Mikolajczyk and Schmid, and Lazebnik, Schmid, and Ponce. Instead of applying the matching technique on a still frame subjected to various image transformations, we will apply this technique to sequential frames of imagery in an urban environment. This approach is intended to be the first of several steps towards eventually integrating a feature-aided tracking option as one of multiple sources of measurement association. The preliminary results show potential signs of success especially with rotation-invariance and move-stop-move transitions; however, additional efforts are required associated with illumination invariance, partial occlusion and disambiguation of close proximity objects.
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Thomas A. Lenz and Juan R. Vasquez "Feature-aided tracking in the urban environment", Proc. SPIE 6969, Signal and Data Processing of Small Targets 2008, 69690D (16 April 2008); https://doi.org/10.1117/12.777398
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