Image-based reconstruction for view-independent human motion recognition

In this paper, we introduce a novel method for employing image-based rendering to extend the range of use of human motion recognition systems. We demonstrate the use of image-based rendering to generate additional training sets for view-dependent human motion recognition systems. Input views orthogonal to the direction of motion are created automatically to construct the proper view from a combination of non-orthogonal views taken from several cameras. To extend motion recognition systems, image-based rendering can be utilized in two ways: (i) to generate additional training sets for these systems containing a large number of non-orthogonal views, and (ii) to generate orthogonal views (the views those systems are trained to recognize) from a combination of non-orthogonal views taken from several cameras. In this case, image-based rendering is used to generate views orthogonal to the mean direction of motion. We tested the method using an existing view-dependent human motion recognition system on two different sequences of motion, and promising initial results were obtained.