Large object detection in cluttered background using boosted Markov Chain Monte Carlo
In this paper, we present a new object detection method using codebook and boosted Markov Chain Monte Carlo (MCMC) estimation. It is relatively well detected using adaboost and simple Haar-like features for small objects. However, the detection problem is more difficult when object size becomes larger (over 150 × 150) due to different surface markings and clutter. Codebook-based object representation and boosted MCMC method can detect large objects robustly. Experimental results validate convincing detection for large objects.