This paper proposes a 3D human body pose reconstruction system based on videos captured from any perspective view of a monocular camera. The appearance, color and temporal information extracted from the video frames are effectively combined to accurately track 2D body features. This view invariant system overcomes the challenges of requiring the modeled human to be viewed from a pre-specified angular perspective so as to initialize the 3D body model configuration, as well as to continuously find the best match between the tracked 2D features with the 3D model based on the downhill simplex algorithm. The matching information of 3D poses are also fed back to assist 2D tracking, which eventually provides more reliable 3D tracking performance.
['Shian-Ru Ke', 'Jenq-Neng Hwang', 'Kung-Ming Lan', 'Shen-Zheng Wang']
View-invariant 3D human body pose reconstruction using a monocular video camera