Active vision
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
Fusing Points and Lines for High Performance Tracking
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
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Augmented reality applications on hand-held devices suffer from the limited available processing power. While methods to detect the location of artificially textured markers within the scene are commonly used, geometric properties of three-dimensional objects are rarely exploited for object tracking. In order to track such geometry efficiently on mobile devices, existing methods must be adapted. By focusing on key behaviors of edge-based models, we present a sparse depth buffer structure to provide an efficient rasterization method. This allows the tracking algorithm to run on a single CPU core of a current-generation hand-held device, while requiring only minimal support from the GPU.