Related Experiment Video
Updated: Apr 18, 2026
08:56
Clinical Assessment of Spatiotemporal Gait Parameters in Patients and Older Adults
Published on: November 7, 2014
14.5K
Class Energy Image analysis for video sensor-based gait recognition: a review.
Zhuowen Lv1, Xianglei Xing2, Kejun Wang3
1College of Automation, Harbin Engineering University, Harbin 150001, China. lvlewen1988@163.com.
Sensors (Basel, Switzerland)
|January 10, 2015
Summary
This review explores Class Energy Images for gait recognition, analyzing their effectiveness and robustness in video-based systems. It offers insights into challenges and future directions for this biometric feature.
Area of Science:
- Computer Vision
- Biometrics
- Pattern Recognition
Background:
- Gait is a unique biometric at distances, crucial for video-based recognition.
- Class Energy Image (CEI) is a key appearance-based gait representation method.
Purpose of the Study:
- To review and analyze various Class Energy Image approaches for gait representation.
- To compare the effectiveness and robustness of CEI methods on benchmark gait databases.
Main Methods:
- Literature review of Class Energy Image expressions and meanings.
- Analysis of information content within Class Energy Images.
- Comparative analysis of CEI method performance on benchmark gait databases.
Main Results:
- Detailed review and analysis of various Class Energy Image approaches.
- Comparative assessment of CEI method effectiveness and robustness.
- Identification of current research challenges in gait representation.
Conclusions:
- Class Energy Image methods are significant for video-based gait recognition.
- This review provides a comprehensive reference for CEI in gait analysis.
- Future research directions for gait representation are outlined.
