Combining multiple evidences for gait recognition

TitleCombining multiple evidences for gait recognition
Publication TypeConference Papers
Year of Publication2003
AuthorsCuntoor N, Kale A, Chellappa R
Conference NameAcoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). 2003 IEEE International Conference on
Date Published2003/04//
Keywordsanalysis;, dynamic, evidences;, extraction;, feature, features;, frontal, Gait, height;, human, identification;, image, MIN, multiple, nonprobabilistic, probabilistic, Product, recognition;, rules;, sets;, side, static, Sum, sway;, swing;, techniques;, views;

In this paper, we systematically analyze different components of human gait, for the purpose of human identification. We investigate dynamic features such as the swing of the hands/legs, the sway of the upper body and static features like height, in both frontal and side views. Both probabilistic and non-probabilistic techniques are used for matching the features. Various combination strategies may be used depending upon the gait features being combined. We discuss three simple rules: the Sum, Product and MIN rules that are relevant to our feature sets. Experiments using four different datasets demonstrate that fusion can be used as an effective strategy in recognition.