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Image acquisition devices can usually only get two-dimensional plane images. It has always been research focus in the field of computer vision that how to quickly and accurately recover motion parameters of objects in space from two-dimensional plane images. In this paper, the 3D pose tracking algorithm of monocular model-based is studied. This paper firstly uses the technology of binocular stereo vision to achieve Three-dimensional reconstruction of the objects and uses a two-step method based on the reweighted brightness depth change constraint equation to solve pose on the frame. The paper adopts the brightness change constraint equation to get the coarse value of 3D pose, and then proposes the reweighted brightness depth method based on Huber function to get the exact value of 3D pose. The paper also presents the multi-frame registration method of view to solve the registration failure problem and eliminate the accumulated error. Experiments results prove a great advantage of real-time and accuracy compared with other systems.
Tong et al. (Tue,) studied this question.