UTD-MHAD
Introduced by Chen Chen et al. in UTD-MHAD: A multimodal dataset for human action recognition utilizing a depth camera and a wearable inertial sensor
The UTD-MHAD dataset consists of 27 different actions performed by 8 subjects. Each subject repeated the action for 4 times, resulting in 861 action sequences in total. The RGB, depth, skeleton and the inertial sensor signals were recorded.
Source: Skepxels: Spatio-temporal Image Representation of Human Skeleton Joints for Action RecognitionBenchmarks
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UTD-MHAD
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PoseMap
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Action Machine
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Papers
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