Robust Visual Tracking from Dynamic Control of Processing

This paper presents a robust tracking system that employs a supervisory controller to dynamically control the selection of processing modules and the parameters used for processing. This system employs multiple pixel level detection operations to detect and track blobs at video rate. Groups of blobs can be interpreted as related components of objects during an interpretation phase. A central supervisor is used to adapt processing parameters so as to maintain reliable real time tracking. System performance is demonstrated on the PETS 04 data set.

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