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Graph based visual object tracking
2009 ISECS International Colloquium on Computing, Communication, Control, and Management, 2009Object tracking is viewed as a two-class “one-versus-rest” classification problem, in which the sample distribution of the target is approximately Gaussian while the background samples are often multi-modal. Based on these special properties, we model the visual appearance via graph approach, which is a semi-supervised approach.
Zhou Guanling, Wang Yuping, Dong Nanping
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2018
Moving object tracking is to find out the candidate object region which is the most similar area in the image sequence through the effective expression of the object, that is to locate the target in the sequence image so as to obtain the complete motion trajectory of the moving target.
Shengrong Gong +5 more
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Moving object tracking is to find out the candidate object region which is the most similar area in the image sequence through the effective expression of the object, that is to locate the target in the sequence image so as to obtain the complete motion trajectory of the moving target.
Shengrong Gong +5 more
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Visual tracking by proto-objects
Pattern Recognition, 2013In this paper, we propose a biologically inspired framework of visual tracking based on proto-objects. Given an image sequence, proto-objects are first detected by combining saliency map and topic model. Then the target is tracked based on spatial and saliency information of the proto-objects. In the proposed Bayesian approach, states of the target and
Zhidong Li +4 more
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Visual tracking of object silhouettes
2009 16th IEEE International Conference on Image Processing (ICIP), 2009In this paper we propose a new method that addresses the problem of tracking the bitmap (silhouette) of an object in a video under very general conditions. We assume a general target, possibly non rigid, with no prior information except initialization.
Guy Boudoukh, Ido Leichter, Ehud Rivlin
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Multiple-object tracking and visually guided touch
Attention, Perception, & Psychophysics, 2021Multiple-object tracking (MOT) involves keeping track of the positions of multiple independent target items as they move among distractors. According to Pylyshyn (Cognition, 80, 127-158, 2001), the item individuation mechanism used in MOT is also used in visually guided touch.
Mallory E, Terry, Lana M, Trick
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Visual Tracking and Object Recognition
IFAC Proceedings Volumes, 2001Abstract In this paper, we will discuss the closely related problems of visual tracking and object recognition. The solution involves adaptive and robust control in conjunction with multiscale methods from signal processing, and shape recognition theory from computer vision.
Allen Tannenbaum +2 more
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OmniTracker: Unifying Visual Object Tracking by Tracking-With-Detection
IEEE Transactions on Pattern Analysis and Machine IntelligenceVisual Object Tracking (VOT) aims to estimate the positions of target objects in a video sequence, which is an important vision task with various real-world applications. Depending on whether the initial states of target objects are specified by provided annotations in the first frame or the categories, VOT could be classified as instance tracking (e.g.
Junke Wang +6 more
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Bayesian Tracking of Visual Objects
2009Tracking objects in image sequences involves performing motion analysis at the object level, which is becoming an increasingly important technology in a wide range of computer video applications, including video teleconferencing, security and surveillance, video segmentation, and editing.
Nanning Zheng, Jianru Xue
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Target Aware Visual Object Tracking
2019We propose a visual object tracker that improves accuracy while significantly decreasing false alarm rate. This is achieved by a late fusion scheme that integrates the motion model of particle sampling with the region proposal network of Mask R-CNN during inference.
Caner Ozer, Filiz Gurkan, Bilge Gunsel
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Efficient framework for extended visual object tracking
2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops), 2011An algorithm for extending the Bayesian multiple target tracking framework to solve the extended visual object tracking problem using sparse features is proposed. In particular, the state space is divided into two sets: one modeling the global motion of the object and one modeling the movement of every feature point.
M. Soto Alvarez +2 more
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