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To overcome the problem of occlusion in visual tracking, this paper proposes an occlusion-aware tracking algorithm. The proposed algorithm divides the object into discrete image patches according to the pixel distribution of the object by…

计算机视觉与模式识别 · 计算机科学 2021-04-19 Rongtai Caiand Peng Zhu

Occlusion is one of the most significant challenges encountered by object detectors and trackers. While both object detection and tracking has received a lot of attention in the past, most existing methods in this domain do not target…

计算机视觉与模式识别 · 计算机科学 2021-06-22 Satyaki Chakraborty , Martial Hebert

Occlusion is a long-standing problem that causes many modern tracking methods to be erroneous. In this paper, we address the occlusion problem by exploiting the current and future possible locations of the target object from its past…

计算机视觉与模式识别 · 计算机科学 2020-10-16 Yuan Liu , Ruoteng Li , Robby T. Tan , Yu Cheng , Xiubao Sui

The problem of multi-object tracking is a fundamental computer vision research focus, widely used in public safety, transport, autonomous vehicles, robotics, and other regions involving artificial intelligence. Because of the complexity of…

计算机视觉与模式识别 · 计算机科学 2022-10-20 Kai Ren , Chuanping Hu

Object segmentation and object tracking are fundamental research area in the computer vision community. These two topics are diffcult to handle some common challenges, such as occlusion, deformation, motion blur, and scale variation. The…

计算机视觉与模式识别 · 计算机科学 2019-04-29 Rui Yao , Guosheng Lin , Shixiong Xia , Jiaqi Zhao , Yong Zhou

Tracking pixels in videos is typically studied as an optical flow estimation problem, where every pixel is described with a displacement vector that locates it in the next frame. Even though wider temporal context is freely available, prior…

计算机视觉与模式识别 · 计算机科学 2022-07-26 Adam W. Harley , Zhaoyuan Fang , Katerina Fragkiadaki

In order to manipulate a deformable object, such as rope or cloth, in unstructured environments, robots need a way to estimate its current shape. However, tracking the shape of a deformable object can be challenging because of the object's…

机器人学 · 计算机科学 2020-11-03 Yixuan Wang , Dale McConachie , Dmitry Berenson

We propose a novel part-based method for tracking an arbitrary object in challenging video sequences. The colour distribution of tracked image patches on the target object are represented by pairs of RGB samples and counts of how many…

计算机视觉与模式识别 · 计算机科学 2019-10-11 George De Ath , Richard M. Everson

Multi-object tracking from RGB-D video sequences is a challenging problem due to the combination of changing viewpoints, motion, and occlusions over time. We observe that having the complete geometry of objects aids in their tracking, and…

计算机视觉与模式识别 · 计算机科学 2020-12-17 Norman Müller , Yu-Shiang Wong , Niloy J. Mitra , Angela Dai , Matthias Nießner

Object tracking can be formulated as "finding the right object in a video". We observe that recent approaches for class-agnostic tracking tend to focus on the "finding" part, but largely overlook the "object" part of the task, essentially…

计算机视觉与模式识别 · 计算机科学 2019-10-28 Achal Dave , Pavel Tokmakov , Cordelia Schmid , Deva Ramanan

Visual object tracking is an active topic in the computer vision domain with applications extending over numerous fields. The main sub-tasks required to build an object tracker (e.g. object detection, feature extraction and object tracking)…

图像与视频处理 · 电气工程与系统科学 2021-10-20 Al-Hussein A. El-Shafie , S. E. D. Habib

Object detection and tracking in videos represent essential and computationally demanding building blocks for current and future visual perception systems. In order to reduce the efficiency gap between available methods and computational…

计算机视觉与模式识别 · 计算机科学 2022-07-27 Issa Mouawad , Francesca Odone

This paper addresses the problem of tracking moving objects of variable appearance in challenging scenes rich with features and texture. Reliable tracking is of pivotal importance in surveillance applications. It is made particularly…

计算机视觉与模式识别 · 计算机科学 2013-09-26 Rhys Martin , Ognjen Arandjelović

Despite the success of many advanced tracking methods in this area, tracking targets with drastic variation of appearance such as deformation, view change and partial occlusion in video sequences is still a challenge in practical…

计算机视觉与模式识别 · 计算机科学 2016-11-15 Suofei Zhang , Zhixin Sun , Xu Cheng , Zhenyang Wu

A robust and fast automatic moving object detection and tracking system is essential to characterize target object and extract spatial and temporal information for different functionalities including video surveillance systems, urban…

计算机视觉与模式识别 · 计算机科学 2017-11-07 Mahdieh Poostchi

Tracking is one of the most important but still difficult tasks in computer vision and pattern recognition. The main difficulties in the tracking field are appearance variation and occlusion. Most traditional tracking methods set the…

计算机视觉与模式识别 · 计算机科学 2016-12-28 Jinho Lee , Brian Kenji Iwana , Shouta Ide , Seiichi Uchida

Recent years have seen an explosion of interest in analyzing the motion of objects in video data as a way for students to connect the concepts of physics to something tangible like a video recording of an experiment. A variety of software…

Visual object tracking is the problem of predicting a target object's state in a video. Generally, bounding-boxes have been used to represent states, and a surge of effort has been spent by the community to produce efficient causal…

计算机视觉与模式识别 · 计算机科学 2021-02-02 Matteo Dunnhofer , Niki Martinel , Christian Micheloni

Most tracking-by-detection methods employ a local search window around the predicted object location in the current frame assuming the previous location is accurate, the trajectory is smooth, and the computational capacity permits a search…

计算机视觉与模式识别 · 计算机科学 2015-12-01 Gao Zhu , Fatih Porikli , Hongdong Li

A fundamental component of modern trackers is an online learned tracking model, which is typically modeled either globally or locally. The two kinds of models perform differently in terms of effectiveness and robustness under different…

计算机视觉与模式识别 · 计算机科学 2016-09-12 Yao Sui , Guanghui Wang , Yafei Tang , Li Zhang
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