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Hybrid Skeleton-Based Motion Templates for Cross-View and Appearance-Robust Gait Recognition.

João Ferreira Nunes1, Pedro Miguel Moreira2, João Manuel R S Tavares3

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Summary

New Gait Skeleton Images (GSIs) offer robust human identification by encoding 3D motion into compact 2D templates. These skeletal descriptors show improved stability across different views and appearances compared to traditional methods.

Keywords:
CASIA-BGRIDDSGait Skeleton Image (GSI)appearance variationcovariate robustnessgait recognitionhuman pose estimationmotion templatesskeleton-based representationviewpoint variation

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Area of Science:

  • Computer Vision
  • Biometrics
  • Human Motion Analysis

Background:

  • Silhouette-based gait recognition (e.g., Gait Energy Image) excels in controlled settings but falters with appearance variations.
  • Skeleton-based methods offer interpretability but are susceptible to pose-estimation inaccuracies.

Purpose of the Study:

  • To introduce novel compact 2D skeletal descriptors, Gait Skeleton Images (GSIs), for enhanced gait recognition.
  • To develop a unified pipeline for processing 3D joint trajectories into static templates compatible with 2D CNNs.
  • To evaluate the robustness and performance of GSIs against appearance and viewpoint changes.

Main Methods:

  • Encoding 3D joint trajectories into line-based and joint-based 2D skeletal templates (GSIs).
  • Implementing a processing pipeline involving topology normalization, view alignment, projection, and rendering.
  • Analyzing core design factors on the GRIDDS dataset and evaluating performance on the CASIA-B dataset.

Main Results:

  • GSI variants demonstrate reduced performance degradation under varying appearance conditions (viewpoint, clothing, carried objects) compared to Gait Energy Images.
  • GSIs exhibit greater stability under severe cross-view gait recognition scenarios.
  • While Gait Energy Images achieve higher same-view accuracy, GSIs offer superior robustness.

Conclusions:

  • Compact skeletal templates like GSIs can effectively complement appearance-based gait recognition methods.
  • The proposed Gait Skeleton Images show promise for improving the robustness of human identification systems.
  • Future advancements in 3D human pose estimation could further enhance the utility of skeletal-template-based gait recognition.