Abstract
In this paper, a basic conceptual architecture aimed at the design of Computer Vision System is qualitatively described. The proposed architecture addresses the design of vision systems in a modular fashion using modules with three distinct units or components: a processing network or diagnostics unit, a control unit and a communications unit. The control of the system at the modules level is designed based on a Discrete Events Model. This basic methodology has been used to design a realtime active vision system for detection, tracking and recognition of people. It is made up of three functional modules aimed at the detection, tracking, recognition of moving individuals plus a supervision module. The detection module is devoted to the detection of moving targets, using optic flow computation and relevant areas extraction. The tracking module uses an adaptive correlation technique to fixate on moving objects. The objective of this module is to pursuit the object, centering it into a relocatable focus of attention window (FOAW) to obtain a good view of the object in order to recognize it. Several focus of attention can be tracked simultaneously. The recognition module is designed in an opportunistic style in order to identify the object whenever it is possible. A demonstration system has been developed to detect, track and identify walking people.
This research is sponsored in part by Spanish CICYT under project TAP95-0288.
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Hernández, M. et al. (1999). DESEO: An Active Vision System for Detection Tracking and Recognition. In: Computer Vision Systems. ICVS 1999. Lecture Notes in Computer Science, vol 1542. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-49256-9_23
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DOI: https://doi.org/10.1007/3-540-49256-9_23
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