AP-Based Adaboost in High Level Feature Extraction at TRECVID
We propose an improved fusion method used in high level feature extraction at TRECVID - average precision based Adaboost (AP-based Adaboost). The AP-based weighting scheme makes use of both the weight and the rank of each sample that all have contribution to the final average precision. The weighting scheme along with the more adaptive formulae modified in our method makes it outperform the standard Adaboost algorithm as well as many other fusion methods. Experimental results on TRECVID-2005 development set show that our method is an effective and relatively robust fusion method.