Software Based Object Tracking with Visual Feature Integration

Ajith Pasqual, Hidenori Takeshima, Kiyoharu Aizawa

Abstract: Multiple visual features can be used to track objects in environments where the use of a single visual feature is not sufficient. We have proposed an alternative method to feature integration by way of feature substitution where the dominant feature at any instant is used for tracking. The problem of increased computational cost resulting from the use of multiple features is addressed by using software optimization techniques. Here we use software threads and special instructions provided in MMX processors to increase the frame rate. Experimental results indicate that it is not always necessary to adopt a hardware based approach for real time object tracking even when the computational cost is high.