Vanishing Point-based Line Sampling for Real-time People Localization

In this paper, we propose a real-time multicamera people localization method based on line sampling of image foregrounds. For each view, these line samples are originated from the vanishing point of lines perpendicular to the ground plane. With these line samples, vertical line samples in the 3-D scene can be reconstructed for potential human locations. After some efficient geometric refinement and filtering procedures, the remaining qualified 3-D line samples are clustered and integrated for the identification of locations and heights of people in the scene. Both indoor and outdoor scenarios are examined to demonstrate the effectiveness of our approach in handling serious occlusion in crowed scenes. The average localization error of less than 15 cm for average viewing distance of 15m suggests that our method can be applied to a broad range of surveillance applications that require the real-time computation of localization without using special hardware for acceleration.

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