Grimage: markerless 3D interactions
ACM SIGGRAPH 2007 emerging technologies
Model based human motion tracking using probability evolutionary algorithm
Pattern Recognition Letters
Real-Time 3D Reconstruction for Occlusion-Aware Interactions in Mixed Reality
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part I
Parallel high resolution real-time visual hull on GPU
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Real-time voxel-based visual hull reconstruction
Microprocessors & Microsystems
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The human activity monitoring is one of the major tasks in the field of computer vision. Recently, not only the 2D images but also 3D shapes of a moving person are desired in kinds of cases, such as motion analysis, security monitoring, 3D video creation and so on. In this paper, we propose a parallel pipeline system on a PC cluster for reconstructing the 3D shape of a moving person in real-time. For the 3D shape reconstruction, we have extended the volume intersection method to the 3-base-plane volume intersection. By thus extension, the computation is accelerated greatly for arbitrary camera layouts. We also parallelized the 3-base-plane method and implemented it on a PC cluster. On each node, the pipeline processing is adopted to improve the throughput. To decrease the CPU idle time caused by I/O processing, image capturing, communications over nodes and so on, we implement the pipeline using multiple threads. So that, all stages can be executed concurrently. However, there exists resource conflicts between stages in a real system. To avoid the conflicts while keeping high percentage of CPU running time, we propose a tree structured thread control model. As a result, We achieve the performance as obtaining the full 3D volumes of a moving person at about 12 frames per second, where the voxel size is 5脳5脳5 [mm^3]. The effectiveness of the thread tree model in such real-time computation is also proved by the experimental results.