Detection and Tracking of Very Small Low Contrast Objects

We present a Kalman tracking algorithm that can track a number of very small, low contrast objects through an image sequence taken from a static camera. The issues that we have addressed to achieve this are twofold. Firstly, the detection of small objects comprising a few pixels only, mov-ing slowly in the image, and secondly, tracking of multiple small targets even though they may be lost either through occlusion or in noisy signal. The ap-proach uses a combination of wavelet filtering for detection with an interest operator for testing multiple target hypotheses based within the framework of a Kalman tracker. We demonstrate the robustness of the approach to oc-clusion and for multiple targets.