LSTCN is a dual-branch CNN that extracts temporal gait features by pooling spatial data into strips and applying local spatiotemporal convolutions with asymmetric kernels.
A general subspace en- semble learning framework via totally-corrective boosting and tensor-based and local patch-based extensions for gait recognition
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Local Spatiotemporal Convolutional Network for Robust Gait Recognition
LSTCN is a dual-branch CNN that extracts temporal gait features by pooling spatial data into strips and applying local spatiotemporal convolutions with asymmetric kernels.