Dahua AI Gait Recognition Breaks CASIA-B Gait Records
Dahua Technology’s gait recognition technology has again broken the record of CASIA-B gait dataset records across multiple parameters.
The average accuracy of Rank1 for NM (normal walking), BG (with a bag) and CL (in a coat) reached 97.4 per cent, 94.0 per cent, and 87.0 per cent respectively, hitting another historical height and maintaining its leading position.
Gait recognition uses body shape and walking posture to identify a person, even if his/her face is occluded. It is one of the biometric recognition technologies with the greatest potential for long distance recognition scenarios.
Aiming to address the technical difficulties of gait recognition in clothing changing search, carrying changing search and cross-view search, Dahua Technology integrates innovation and application of multi-modal gait algorithms, local gait feature extraction, and spatio-temporal gait feature extraction technologies.
Combined with powerful model training and object recognition, it greatly improves the algorithm’s robustness in special scene applications such as clothing changing, similar clothing, facial occlusion, and facial disguise, making the gait recognition analysis more accurate and efficient.
Dahua Technology has received numerous first-place recognitions in various global AI ranking categories, including scene parsing, binocular stereo matching, remote sensing image analysis, person re-identification and visual target tracking algorithms.