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Updated: Apr 18, 2026

Clinical Assessment of Spatiotemporal Gait Parameters in Patients and Older Adults
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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
PubMed
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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:

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  • 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.