Moving shadow detection with low- and mid-level reasoning

In this paper, we propose a multi-level shadow identification scheme which is generally applicable without restrictions on the number of light sources, illumination conditions, surface orientations, and object sizes. In the first level, we use a background segmentation technique to identify foreground regions which include moving shadows. In the second step, pixel-based decisions are made by comparing the current frame with the background model to distinguish between shadows and actual foreground. In the third step, this result is improved using blob-level reasoning which works on geometric constraints of identified shadow and foreground blobs. Results on various indoor and outdoor sequences under different illumination conditions show the success of the proposed approach.