Journal ArticleDOI
Video object tracking using adaptive Kalman filter
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TLDR
The proposed method has the robust ability to track theMoving object in the consecutive frames under some kinds of real-world complex situations such as the moving object disappearing totally or partially due to occlusion by other ones, fast moving object, changing lighting, changing the direction and orientation of the movingobject, and changing the velocity of moving object suddenly.About:
This article is published in Journal of Visual Communication and Image Representation.The article was published on 2006-12-01. It has received 314 citations till now. The article focuses on the topics: Video tracking & Kalman filter.read more
Citations
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Book ChapterDOI
Deep Siamese Networks with Bayesian non-Parametrics for Video Object Tracking
Anthony D. Rhodes,Manan Goel +1 more
TL;DR: A novel algorithm utilizing a deep Siamese neural network as a general object similarity function in combination with a Bayesian optimization framework to encode spatio-temporal information for efficient object tracking in video offers several benefits over current state of the art video tracking methods.
Journal ArticleDOI
Shallow Layer Convolutional Features with Correlation Filters for UAV Object Tracking
TL;DR: Based on the comprehensive experimental results, the proposed method performs favorably against state-of-the-art tracking algorithms.
Book ChapterDOI
Anti-occlusion Video Target Tracking Based on Double Threshold Judgment
Ying Zhang,Fang-cang Du,Ke Xu +2 more
TL;DR: An anti-occlusion video target tracking method based on double threshold judgment, which combines Discriminative Scale Space Tracking (DSST) algorithm and Kalman filtering algorithm, according to the change of correlation coefficient P between adjacent templates is proposed.
Patent
System and method for detection and visualization of anomalous media events
TL;DR: In this article, a system for detection and visualization of anomalous media events is described, where AV media data of a sporting event (game) are analyzed to identify AV media segments indicative of unscripted anomalous events (AE's) that elicit a social media response (SMR), and selectable AE graphic visualization (or AE GUI) is provided showing the position of the AE on the court or field of play graphic, corresponding to the actual field-of play, as a form of augmented reality.
Proceedings ArticleDOI
Multiple object tracking via a two-way confidence-based correspondence algorithm
Hadi Firouzi,Homayoun Najjaran +1 more
TL;DR: An efficient object correspondence algorithm for tracking multiple objects in dynamic environments is presented and the results show the efficiency and reliability of the method against a large number of objects.
References
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BookDOI
An Introduction to the Kalman Filter
Greg Welch,Gary Bishop +1 more
TL;DR: The discrete Kalman filter as mentioned in this paper is a set of mathematical equations that provides an efficient computational (recursive) means to estimate the state of a process, in a way that minimizes the mean of the squared error.
Journal ArticleDOI
A Survey of Computer Vision-Based Human Motion Capture
Thomas B. Moeslund,Erik Granum +1 more
TL;DR: A comprehensive survey of computer vision-based human motion capture literature from the past two decades is presented, with a general overview based on a taxonomy of system functionalities, broken down into four processes: initialization, tracking, pose estimation, and recognition.
Proceedings ArticleDOI
Moving target classification and tracking from real-time video
TL;DR: An end-to-end method for extracting moving targets from a real-time video stream, classifying them into predefined categories according to image-based properties, and then robustly tracking them is described.
Journal ArticleDOI
Robust online appearance models for visual tracking
TL;DR: A framework for learning robust, adaptive, appearance models to be used for motion-based tracking of natural objects to provide robustness in the face of image outliers, while adapting to natural changes in appearance such as those due to facial expressions or variations in 3D pose.
Book ChapterDOI
Stochastic Tracking of 3D Human Figures Using 2D Image Motion
TL;DR: A probabilistic method for tracking 3D articulated human figures in monocular image sequences that relies only on a frame-to-frame assumption of brightness constancy and hence is able to track people under changing viewpoints, in grayscale image sequences, and with complex unknown backgrounds.