Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
Bundle Adjustment - A Modern Synthesis
ICCV '99 Proceedings of the International Workshop on Vision Algorithms: Theory and Practice
ASSET-2: real-time motion segmentation and shape tracking
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Contour-Based Object Tracking with Occlusion Handling in Video Acquired Using Mobile Cameras
IEEE Transactions on Pattern Analysis and Machine Intelligence
Prakash: lighting aware motion capture using photosensing markers and multiplexed illuminators
ACM SIGGRAPH 2007 papers
Speeded-Up Robust Features (SURF)
Computer Vision and Image Understanding
Self-identifying patterns for plane-based camera calibration
Machine Vision and Applications
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This paper presents a new algorithm for obtaining inter-frame and inter-view (inter-camera) correspondences to solve the problem of tracking an object labeled with infrared markers using a stereo pair taken simultaneously in the infrared region. In practice it is often necessary to track an object when it is impossible to have contact with it, for example, the tracking of facial movements using the motion capture technique (Motion Capture, [9, 10]) to create realistic animation or the tracking of object movements when interacting with the augmented reality. In such cases contactless object tracking methods are used. In the classic version of this problem, two or more cameras are used to capture the object of interest. In order to restore three-dimensional coordinates of object points, it is necessary to triangulate the received projections of the points. In the case of the visible range, the problem of finding and matching points on the object can be solved using interest point descriptors [2]. However, there are situations in which it is impossible to use the visible range data, for example, a uniformly colored or regularly textured object, which makes it senseless to use interest point descriptors. Thus, the use of interest point descriptors significantly limits the scope of application of algorithms because of the imposition of severe restrictions on the class of tracked objects, objects should have uneven texture. In turn, the motion capture method implies the tracking of an object of a predetermined shape, when it is not always possible to establish its shape. In this work, an alternative approach is proposed, i.e., the use of infrared markers and cameras that capture frames in the infrared range which makes the task of finding critical points irrelevant. On the other hand, infrared markers on cameras that operate in the infrared range are indistinguishable from each other. Therefore, there is the problem of finding correspondences which in the case of interest point descriptors is solved by the very nature of the descriptors. In this paper, we describe algorithms that make it possible to restore point correspondences by a sequence of stereo pair images (Fig. 1) and its calibrations. In this case, epipolar constraints and a voting scheme based on the greedy algorithm are used.