Browsing the environment with the SNAP&TELL wearable computer system
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We propose to evaluate our sparsity driven people localization framework on crowded complex scenes. The problem is recast as a linear inverse problem. It relies on deducing an occupancy vector, i.e. the discretized occupancy of people on the ground, from t ...
Despite the large success of games grounded on movement-based interactions the current state of full body motion capture technologies still prevents the exploitation of precise interactions with complex environments. This paper focuses on ensuring a precis ...
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A novel approach is presented to locate dense crowd of people in a network of fixed cameras given the severely degraded background subtracted silhouettes. The problem is formulated as a sparsity constrained inverse problem using an adaptive dictionary cons ...
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This paper presents an all-airborne approach for the geometric self-calibration of medium format digital cameras used in direct georeferencing. The motivation for this research was the problems of variation of distortion within the photographic field and h ...
In recent years, we have seen a dramatic increase in the amount of video data recorded and stored around the world. Driven by the availability of low-cost video cameras, the ever-decreasing cost of digital media storage, and the explosion in popularity of ...
In recent years, we have seen a dramatic increase in the amount of video data recorded and stored around the world. Driven by the availability of low-cost video cameras, the ever-decreasing cost of digital media storage, and the explosion in popularity of ...
This thesis proposes a Chamfer-based method for human body pose detection that combines silhouette matching, motion information, and statistical relevance estimates in an original way. We demonstrate that our method can not only detect people but also reco ...
