An evaluation of monocular image stabilization algorithms for automotive applications

The performance of many computer vision applications, especially in the automotive field, can be greatly increased if camera oscillations induced by movements of the acquisition devices are corrected by a stabilization system. An effective stabilizer should cope with different oscillation frequencies and amplitude intervals, and work in a wide range of environments (such as urban, extra-urban or even unstructured ones). In this paper we analyze three different approaches, based on signature, feature, and correlation tracking respectively, that have been devised to face these problems