Abstract
This paper presents a novel method for gait-based person identification robust to changes in appearance. Gait is sensitive to appearance changes, such as variations of clothes and carrying conditions, so the correct classification rate is reduced in case target's appearance condition is different from that in the database. So we propose a new part-based person identification method, where the discrimination capability at each part is directly controlled based on gait features between gallery datasets and probe dataset. Experiments using a gait database CASIA show the effectiveness of the proposed method.
