Robust gait-based gender classification using depth cameras
- PDF / 1,338,665 Bytes
- 11 Pages / 595 x 794 pts Page_size
- 34 Downloads / 212 Views
RESEARCH
Open Access
Robust gait-based gender classification using depth cameras ` Laura Igual1,3* , Agata Lapedriza2,3 and Ricard Borr`as3
Abstract This article presents a new approach for gait-based gender recognition using depth cameras, that can run in real time. The main contribution of this study is a new fast feature extraction strategy that uses the 3D point cloud obtained from the frames in a gait cycle. For each frame, these points are aligned according to their centroid and grouped. After that, they are projected into their PCA plane, obtaining a representation of the cycle particularly robust against view changes. Then, final discriminative features are computed by first making a histogram of the projected points and then using linear discriminant analysis. To test the method we have used the DGait database, which is currently the only publicly available database for gait analysis that includes depth information. We have performed experiments on manually labeled cycles and over whole video sequences, and the results show that our method improves the accuracy significantly, compared with state-of-the-art systems which do not use depth information. Furthermore, our approach is insensitive to illumination changes, given that it discards the RGB information. That makes the method especially suitable for real applications, as illustrated in the last part of the experiments section. 1 Introduction Recently, human gait recognition from a medium distance has been attracting more attention. The automatic processing of this type of information has multiple applications, including medical ones [1] or its use as a biometric [2]. Beyond other biometrics such as face, iris, or finger-prints, gait patterns give information about other characteristics (for instance, gender or age) making its analysis interesting for multiple applications. Some enterprises are developing methods for automatically collecting population statistics in railway stations, airports, or shopping malls [3], while marketing departments are working on the development of interactive and personalized advertising. In these contexts, and for these goals, gait is an information source that is particularly appropriate, given that it can be acquired in a non-intrusive way and is accessible even at low resolutions [4]. This is illustrated in Figure 1, where we can see two images captured by a camera located at the entrance of a shopping mall. In this situation, it is very difficult to perform an accurate face *Correspondence: [email protected] 1 Department of Apply Mathematics and Analysis, Universitat de Barcelona, 08007 Barcelona, Spain 3 Computer Vision Center, O Building, UAB Campus, 08193 Bellaterra, Barcelona, Spain Full list of author information is available at the end of the article
analysis to extract characteristics of the subjects visiting the mall, because of the view angle, the low resolution of the faces, and the illumination conditions. However, some interesting information about the subjects can be extracted by analyzing the body figure and the w
Data Loading...
