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, moving 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 approach 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 occlusion and for multiple targets.

• Type: Conference
• Year: 1998
• Where: BMVC
• Authors: D. Davies, Phil L. Palmer, Majid Mirmehdi
• Keywords: BMVC 1998, Computer Vision, Kalman Tracking Algorithm, Multiple Small Targets, Multiple Targets