Abstract
Traditionally, tracking systems require dedicated hardware to handle the computational demands and input/output rates imposed by real-time video sources. An alternative presented in this paper uses configurable computing machines, which use interconnected FPGAs to provide fine-grain parallelism and reconfigurability so that high-speed performance is possible for many different applications. The efficacy of such architectures to image-based computing is illustrated here through the implementation of a tracking system that consists of two parts: a Gaussian pyramid generator and a correlation-based tracker. The pyramid generator converts each input image to a hierarchy of images, each representing the original image at a different resolution. An object is tracked on successive frames by a coarse-to-fine search through this image hierarchy, using the sum of absolute differences as the matching criterion. Splash 2 performs these operations at rates of 15 or 30 frames per second. Its performance therefore rivals that of application-specific systems, although the architecture is inherently general-purpose in nature.
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© 1998 Springer-Verlag Berlin Heidelberg
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Pudipeddi, B., Abbott, A.L., Athanas, P.M. (1998). A configurable computing approach towards real-time target tracking. In: Rolim, J. (eds) Parallel and Distributed Processing. IPPS 1998. Lecture Notes in Computer Science, vol 1388. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-64359-1_677
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DOI: https://doi.org/10.1007/3-540-64359-1_677
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