Simon Smith Jamie Hutton Thomas Moore David Newman

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Presentation transcript:

Simon Smith Jamie Hutton Thomas Moore David Newman Gait Recognition Simon Smith Jamie Hutton Thomas Moore David Newman

Outline Gait? Enrolment Symmetry Hu Invariant Moments Classification Conclusions Demonstration

Gait? From Old Norse gata for “path” Why use gait as a biometric? But possibly from Northern derivative of goat Why use gait as a biometric? Non-invasive Process sequence of images More information than other biometrics Greater robustness/reliability Gait recognition methods Model-based Holistic approach

Holistic Methods Chose to implement two holistic approaches Less computationally complex, faster More suitable for online demonstration A simple representation of Gait Raw numbers, images Problems with occlusion, noise

Enrolment Capture subject’s gait Process video of subject walking Video ideally with chroma-key background Avoid occlusion of subject Outdoor images cause some problems Process video of subject walking Background subtraction Indoor – Chroma-key, Outdoor – Mixture of Gaussians Binary silhouette of each frame ~30 frames captures complete gait cycle Begin at known heel-strike

Symmetry Crop and resize images to 64x64 Centre the body in the image Extract symmetry for each image in sequence Average all symmetry maps to get Gait Signature Compare Gait signatures directly + + + = Number of images

Hu Invariant Moments Shape descriptor, combines moments to give invariance to Rotation Translation Scaling Originally designed for single shape description, extended here for sequences We use Hu1, Hu2 and Hu8 moments Other moments fail to discriminate between subjects

Classification k Nearest Neighbours classification Euclidean distance Up to 6-dimensional feature space Mean of 1 or all Hu moments Variance of 1 or all Hu moments Tie Resolution Highest ranking matches chosen

Conclusions Evaluation of two Holistic Gait descriptors Hu Moments Good indoor performance Poor performance outdoor Needs higher dimensional parameter space Ability to ignore/correct anomalous results Symmetry Good indoor, better outdoor performance Larger population may cause poor performance

Demonstration