Visual attention based on a joint perceptual space of color and brightness for improved video tracking

• Visual attention model based on joint perceptual space of color and brightness.
• Computational model derived from theoretical perceptual model.
• Visual attention model extracts more discriminant visual features.
• Practical application to video tracking.
• Experimental comparison against alternative visual attention models.

This paper proposes a new visual attention model based on a joint perceptual space of both color and brightness, and shows that this model is able to extract more discriminant visual features, especially when dealing with objects that are very similar visually. That joint color and brightness space is based on a biologically inspired theoretical perceptual model originally proposed by Izmailov and Sokolov in the scope of psychophysics. The present paper proposes a computational model that allows the application of Izmailov and Sokolov's theoretical model to digital images, since the original model can only be applied to perceptual data directly drawn from psychophysical experiments. Experimental results with real video sequences show that the proposed visual attention model yields significantly more accurate results in the particular application scope of video tracking than well-known visual attention models that process color and brightness separately.