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
Coupled detection, association and tracking for Traffic Sign Recognition
TL;DR: This paper presents an integrated object detection, association and tracking approach based on a spatio-temporal data fusion that tracks detected sign candidates in order to reduce false positives in tracking-based Traffic Sign Recognition systems.
Journal ArticleDOI
Collaborative Tracking for Multiple Objects in the Presence of Inter-Occlusions
Jingjing Xiao,Mourad Oussalah +1 more
TL;DR: A robust color-based tracker whose model is updated by online learned contextual information is suggested, and a recursive method is performed to improve the estimation accuracy and the robustness to cluttered environment.
Journal ArticleDOI
Improved Deer Hunting Optimization Algorithm for Video- based Salient Object Detection
TL;DR: The investigational analysis of developed Improved-DHO based on the performance measures exposes that the developed improved-D HO obtained a maximum accuracy, specificity, and sensitivity in salient object detection.
Proceedings ArticleDOI
Multiple object tracking by improved KLT tracker over SURF features
TL;DR: The proposed object tracking method is capable of dealing with multiple challenges like illumination changes, variable and uneven background and poor lighting condition and is tested on challenging datasets like ALOV++ and Honda/UCSD compared to the state-of-the-art.
Journal ArticleDOI
Motion Guided Siamese Trackers for Visual Tracking
TL;DR: A motion model and a discriminative model are proposed for motion guided Siamese trackers that outperform the baseline trackers and achieve the state-of-the-art performance, especially in the background clutters scenarios.
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.