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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Proceedings ArticleDOI
Adaptively target tracking method based on double-Kalman filter in existence of outliers
TL;DR: A new target tracking method based on double-Kalman filter in existence of outliers is presented, which can solve above problems by adaptively adjusting the measurement noise covariance based on the two results of Kalman filter with the different steps.
Journal ArticleDOI
Efficient Online Tracking-by-Detection With Kalman Filter
Siyuan Chen,Chenhui Shao +1 more
TL;DR: In this paper, a Kalman-intersection-over-union (KIOU) tracker was proposed for real-time multi-object tracking in videos, which integrates a KF with IOU-based track association methods.
Journal ArticleDOI
Person Re-identification in Videos by Analyzing Spatio-temporal Tubes
TL;DR: In this paper, a hierarchical re-identification framework is proposed and used to rank the output tubes of spatio-temporal frame sequences or tubes of moving persons and performs the re-ID in quick time.
Proceedings ArticleDOI
Sequential Monte Carlo-based fidelity selection in dynamic-data-driven adaptive multi-scale simulations (DDDAMS)
Nurcin Celik,Young Jun Son +1 more
TL;DR: A Sequential Monte Carlo method (sequential Bayesian inference technique) is proposed and embedded into the simulation to enable its ideal fidelity selection given massive datasets.
Book ChapterDOI
Detection and tracking of multiple similar objects based on color-pattern
Hadi Firouzi,Homayoun Najjaran +1 more
TL;DR: An efficient and applicable approach for tracking multiple similar objects in dynamic environments is proposed and the result of the algorithm on real data shows the efficiency and reliability of the proposed method.
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.