We overview a previously reported method for spatial-temporal human gesture recognition under degraded environmental conditions using three-dimensional (3D) integral imaging (InIm) technology with correlation filters. The degraded conditions include low illumination environment and occlusion in front of the human gesture. The human gesture is captured by passive integral imaging, the signal is then processed using computational reconstruction algorithms and denoising algorithms to decrease the noise and remove partial occlusion. Gesture recognition is finally processed using correlation filters. Experimental results show that the proposed approach is promising for human gesture recognition under degraded environmental conditions compared with conventional recognition algorithms.
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