Multimodal Multipart Learning for Action Recognition in Depth Videos

The articulated and complex nature of human actions makes the task of action recognition difficult. One approach to handle this complexity is dividing it to the kinetics of body parts and analyzing the actions based on these partial descriptors. We propose a joint sparse regression based learning method which utilizes the structured sparsity to model each action as a combination of multimodal features from a sparse set of body parts. To represent dynamics and appearance of parts, we employ a heterogeneous set of depth and skeleton based features. The proper structure of multimodal multipart features are formulated into the learning framework via the proposed hierarchical mixed norm, to regularize the structured features of each part and to apply sparsity between them, in favor of a group feature selection. Our experimental results expose the effectiveness of the proposed learning method in which it outperforms other methods in all three tested datasets while saturating one of them by achieving perfect accuracy

Recaptured photo detection using specularity distribution

Detection of planar surfaces in a generic scene is difficult when the illumination is complex and less intense, and the surfaces have non-uniform colors (e.g., a movie poster). As a result, the specularity, if appears, is superimposed with the surface color pattern, and hence the observation of uniform specularity is no longer sufficient for identifying planar sur-faces in a generic scene as it does under a distant point light source. In this paper, we address the problem of planar sur-face recognition in a single generic-scene image. In partic-ular, we study the problem of recaptured photo recognition as an application in image forensics. We discover that the specularity of a recaptured photo is modulated by the micro-structure of the photo surface, and its spatial distribution can be used for differentiating recaptured photos from the origi-nal photos. We validate our findings in real images of generic scenes. Experimental results show that there is a distinguish-able feature of natural scene and recaptured images. Given the definition of specular ratio as the percentage of specularity in the overall measured intensity, the distribution of specular ra-tio image’s gradient of natural images is Laplacian-like while that of recaptured images is Rayleigh-like. Index Terms — Image forensics, recaptured photo detec-tion, dichromatic reflectance model, specularity 1