Perspective distortion modeling in face images and object tracking library.
详细信息
文摘
In a first chapter we describe a method to model perspective distortion as a one- parameter family of warping functions. This can be used to mitigate its effects on visual recognition,or interactively manipulate the perceived personality. The warps are learned from a novel face dataset and,by comparing orbits spanned by images instead of images themselves,we improve face recognition when small focal lengths are used. Additional applications are presented to image editing,videoconference,and multi-view validation of recognition systems. A second chapter is devoted to a new versatile and modular open-source cross- platform online object tracking library,designed to be easily usable by the vision community. Object tracking plays a central part in a number of vision problems,and there is no,to date,a ready-to-use and extensible tracking library at the object level.