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In this paper, we propose a novel approach for handling the occlusion problem in pedestrian detection through optical principles. Our proposed framework is based on a popular three-dimensional imaging technique in optics, named integral imaging, in which multiple viewpoint images captured from a three-dimensional scene are used to extract range information of the scene. The proposed approach effectively reconstructs an unobstructed view of heavily occluded pedestrians simultaneously containing range information. The range information provided by our method can be used for foreground extraction and the reconstruction output can be used in various applications, such as people detection and... 

In this paper, a novel approach for foreground extraction has been proposed based on a popular three-dimensional imaging technique in optics, called integral imaging. In this approach, multiple viewpoint images captured from a three-dimensional scene are used to extract range information of the scene and effectively extract an object or a person, even in the presence of heavy occlusion. The algorithm consists of two parts: depth estimation and reconstruction of the targeted object at the estimated depth distance. Further processing of the resulting reconstructed image can lead to the detection of a face or a pedestrian in the scene, which may not otherwise be detectable due to partial...