Empirical reliability analysis of disparity-based autofocus

Conventional autofocus methods based on contrast detection are often unable to reliably decide the direction of initial lens movement. In this paper, we show that even using the disparity data obtained from blurry stereo images can effectively solve the problem. This approach is developed for stereo cameras with adjustable focal distance. Such stereo cameras provide sharp images over a wide range of object distance. The disparity-based autofocus approach allows the lens to instantly come to a position near the in-focus position or inside the rising zone of the focus profile. We investigate the impact of disparity variation on the first lens movement driven by disparity-based autofocus and suggest how it can be integrated with contrast detection autofocus.