A computationally efficient importance sampling tracking algorithm
This paper proposes a computationally efficient importance sampling algorithm applicable to computer vision tracking. The algorithm is based on the CONDENSATION algorithm, but it avoids expensive operations that are costly in real-time embedded systems. It also includes a method that reduces the number of particles during execution and a new resampling scheme. Our experiments demonstrate that the proposed algorithm is as accurate as the CONDENSATION algorithm. Depending on the processed sequence, the acceleration with respect to CONDENSATION can reach 7\(\times \) for 50 particles, 12\(\times \) for 100 particles and 58\(\times \) for 200 particles.
condensation algorithm video tracking particle filter