Human Identification by Gait using k-mean Clustering Algorithm and Dynamic Time Warping
محل انتشار: دوازدهمین کنفرانس سالانه انجمن کامپیوتر ایران
سال انتشار: 1385
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 2,161
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شناسه ملی سند علمی:
ACCSI12_312
تاریخ نمایه سازی: 23 دی 1386
چکیده مقاله:
Gait Recognition refers to automatic identification of an individual based on his/her style of walking; it's a new biometrics recognition technology. This paper describes a new approach to gait recognition based on kmean clustering algorithm. Body silhouette is extracted by a simple background subtraction, and the clustering is performed to partition image sequence into clusters, so the vectors of feature can be extracted. The recognition is achieved by dynamic time warping technique. We evaluate the proposed gait recognition method on the Gait Challenge database of the University of South Florida (USF), and the experimental results demonstrate that our approach has a good recognition performance.
کلیدواژه ها:
نویسندگان
Amiri
Department of Computer Engineering, Faculty of Computer Engineering, Islamic Azad University-Zanjan Branch، Department of Computer Engineering, PhD Student, Iran University of Science and Technology
Fathy
Department of Computer Engineering, Faculty of Computer Engineering, Iran University of Science and Technology
Tahery
Department of Computer Engineering, Faculty of Computer Engineering, Islamic Azad University-Zanjan Branch