Results 221 to 230 of about 63,873 (257)

Tracking multiple objects in 3D

Proceedings 1999 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human and Environment Friendly Robots with High Intelligence and Emotional Quotients (Cat. No.99CH36289), 2003
A system for tracking multiple targets in 3D is described. The system is made up of two pan-and-tilt units that are attached to the extremities of a rotating arm. This configuration has several advantages and can deal with several specific instances of tracking more than one target.
João Pedro Barreto 0001, Paulo Peixoto, Jorge Batista 0001, Helder Araújo   +3 more
openaire   +1 more source

Tracking multiple objects in terrain

SMC'98 Conference Proceedings. 1998 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.98CH36218), 2002
The digitized battlefield of the 21st Century will revolutionize the methods used to maintain military command and control. The tremendous amount of data available will necessitate the use of intelligent automated systems that augment, and in some cases replace, the human structures currently in place.
Edward Sobiesk, John A. Hamilton Jr., John A. Marin, Donald E. Brown, Maria L. Gini   +4 more
openaire   +1 more source

Multiple object tracking with extended occlusions

Quarterly Journal of Experimental Psychology, 2022
In everyday life, we often view objects through a limited aperture (e.g., soccer players on TV or cars slipping into our blind spot on a busy road), where objects often move out of view and reappear in a different place later. We modelled this situation in a series of multiple object tracking (MOT) experiments, in which we introduced a cover on the ...
Jiří Lukavský, Lauri Oksama, Filip Děchtěrenko   +2 more
openaire   +3 more sources

Recursive Clustering for Multiple Object Tracking

2006 International Conference on Image Processing, 2006
In this paper, we propose a method to track multiple deformable objects in video sequences using a recursive clustering scheme. In a first step, a set of Gabor filter banks is used to filter the difference image between two consecutive frames. Then, the moving areas are sampled by randomly positioning particles in high magnitude area of the filtered ...
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Segmentation and tracking of multiple video objects

Pattern Recognition, 2007
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Andrea Colombari, Andrea Fusiello, Vittorio Murino   +2 more
openaire   +3 more sources

A survey on multiple object tracking algorithm

2016 IEEE International Conference on Information and Automation (ICIA), 2016
Visual Multiple Object Tracking (VMOT) is an important computer vision task which has gained increasing attention due to its academic and commercial potential. There are many different approaches have been proposed to solve the problem. Compared with single object tracking which focuses on appearance model, motion model and other factors, multiple ...
Litong Fan, Zhongli Wang, Baigen Cai, Chuanqi Tao, Zhiyi Zhang, Yinling Wang, Shanwen Li, Fengtian Huang, Shuangfu Fu, Feng Zhang   +9 more
openaire   +1 more source

Object tracking using multiple fragments

2009 16th IEEE International Conference on Image Processing (ICIP), 2009
This paper presents a low-cost tracking algorithm based on multiple multiple fragments, increasing robustness with respect to partial occlusions. Given the initial template representing the desired target, each pixel is classified into a different cluster based on a Mixture of Gaussians (MOG) model, and a set of disjoint fragments is created.
Cláudio Rosito Jung, Amir Said
openaire   +1 more source

Generic multiple object tracking

2015
Multiple object tracking is an important problem in the computer vision community due to its applications, including but not limited to, visual surveillance, crowd behavior analysis and robotics. The difficulties of this problem lie in several challenges such as frequent occlusion, interaction, high-degree articulation, etc.
openaire   +3 more sources

Multiple Feature Fusion for Object Tracking

2012
In this paper, we propose a novel object tracking method by fusing multiple features. The tracking task is formulated under Bayesian inference framework. The posterior probability is resolved by the sum of weighted likelihood observations. Graph based semi-supervised learning method is used for likelihood evaluation, and the distance between foreground
Yu Zhou 0025, Cong Rao, Qin Lu 0001, Xiang Bai, Wenyu Liu 0001   +4 more
openaire   +1 more source

Multiple Planar Object Tracking

2023 IEEE/CVF International Conference on Computer Vision (ICCV), 2023
Zhicheng Zhang, Shengzhe Liu, Jufeng Yang   +2 more
openaire   +1 more source