In this paper, we introduce a novel method for employingimage-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.
Bodor, Robert; Jackson, Bennett; Masoud, Osama.
Image-Based Reconstruction for View-Independent Human Motion Recognition.
Retrieved from the University of Minnesota Digital Conservancy,
Content distributed via the University of Minnesota's Digital Conservancy may be subject to additional license and use restrictions applied by the depositor.