Title :
Gender Recognition Studying by Gait Energy Image Classification
Author :
Juang, Li-Hong ; Lin, Shin-An ; Wu, Ming-Ni
Author_Institution :
Dept. of Aerosp. & Syst. Eng., Feng Chia Univ., FCU, Taichung, Taiwan
Abstract :
To detect human sex from complex background, illumination variations and objects by machine is very difficult but important for adaptive information service. In this research, we present a preliminary design and experimental results of gender recognition from walking movements that utilizes gait energy image(GEI) with denoised energy image(DEI) pre-processing as support vector machine(SVM) classifier to training and extract the characteristics. The result shows that the proposed method would adopt the few characteristic value but the accuracy can reach to 100%.
Keywords :
feature extraction; image classification; image denoising; image motion analysis; object detection; support vector machines; DEI preprocessing; GEI; SVM classifier; adaptive information service; complex background; denoised energy image; gait energy image classification; gender recognition; human sex detection; illumination variation; support vector machine; walking movement; Accuracy; Feature extraction; Humans; Image recognition; Legged locomotion; Support vector machines; Training; Denoised energy image; Gait energy image; Support vector machine;
Conference_Titel :
Computer, Consumer and Control (IS3C), 2012 International Symposium on
Conference_Location :
Taichung
Print_ISBN :
978-1-4673-0767-3
DOI :
10.1109/IS3C.2012.215
