Adaptive detection for tracking moving biological objects in video microscopy sequences

We present a method to detect and track multiple moving biological objects in images acquired by video microscopy. The automatic detection is based upon the correlation of the image with a filter which varies adaptively to represent an object as it moves and deforms. The tracking is performed using a Kalman filter and a cost function which enable the position of the moving objects to be predicted, refined and updated. The efficiency of the method has been tested on real biological image sequences and is illustrated by results obtained from the analysis of typical biological video microscopy sequences.