Background Subtraction Using Illumination-Invariant Structural Complexity
Wonjun Kim, Youngsung Kim · IEEE Signal Processing Letters · 2016
In this letter, we propose a novel method for background subtraction in outdoor scenes. Inspired by the observation that the orthogonal decomposition onto a set of pixel intensities efficiently reveals illumination effects, we exploit a simple, yet powerful feature for describing the underlying structure of the local region in a given video, the so-called illumination-invariant structural complexity (IISC). In contrast to previous approaches still suffering from high-level false positives driven by varying illuminations in outdoor environments, our IISC feature has an ability to greatly discriminate structural changes by moving objects from those by illumination effects. We also provide the theoretical analysis to confirm that the proposed IISC feature is useful for modeling the background under diverse lighting conditions. Moreover, our framework does not require any preprocessing task. Experimental results on various datasets demonstrate that the proposed method is effective for video surveillance in a wide range of outdoor environments.