Histogram-based Detection of Moving Objects for Tracker Initialization in Surveillance Video

We present an approach to localized object detection that is not dependent upon background image construction or object modeling. It is designed to work through camera embedded software using spare processing capacity in a visual signal processor. It uses a localized temporal difference change detector and a particle filter type likelihood to detect possible trackable objects, and to find a point within a detected object at which a particle filter tracker might be initialized.