Multi-Shot Person Re-Identification Approach Based Key Frame Selection

摘要

This paper presents a novel approach to solve the problem of person re-identification in non-overlapping camera views. We propose an appearance based method for person re-identification that condenses a set of frames of the same individual into the multi-class classifier SVM (Support Vector Machine). Still, the choice of different and most expressive frames for each target is very challenging. Besides, efficient person re-identification algorithms are computationally expensive due to the big amount of data used. One of the originalities of our method is how to select different shots during person tracking within each camera to guaranty efficient person re-identification. We evaluate our approach on the publicly available PRID 2011 multi-shot re-identification dataset and demonstrate some performance in comparison with the elimination of the proposed key frames selection.