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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Posted Content
Recurrent Network Models for Human Dynamics
TL;DR: The Encoder-Recurrent-Decoder (ERD) model is a recurrent neural network that incorporates nonlinear encoder and decoder networks before and after recurrent layers that extends previous Long Short Term Memory models in the literature to jointly learn representations and their dynamics.
Proceedings ArticleDOI
Recurrent Network Models for Human Dynamics
TL;DR: In this paper, the Encoder-Recurrent-Decoder (ERD) model is proposed for recognition and prediction of human body pose in videos and motion capture, which is a recurrent neural network that incorporates nonlinear encoder and decoder networks before and after recurrent layers.
Proceedings ArticleDOI
A multiple object tracking method using Kalman filter
TL;DR: An algorithm of feature-based using Kalman filter motion to handle multiple objects tracking is proposed and shows that the algorithm achieves efficient tracking of multiple moving objects under the confusing situations.
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Heterogeneous Association Graph Fusion for Target Association in Multiple Object Tracking
TL;DR: A heterogeneous association graph is constructed that fuses high-level detections and low-level image evidence for target association and the novel idea of adaptive weights is proposed to analyze the contribution between motion and appearance.
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Learning Visual Predictive Models of Physics for Playing Billiards
TL;DR: In this paper, an agent can be equipped with an internal model of the dynamics of the external world, and how it can use this model to plan novel actions by running multiple internal simulations ("visual imagination").
References
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Journal ArticleDOI
Tracking multiple humans in complex situations
Tao Zhao,Ramakant Nevatia +1 more
TL;DR: This work shows how multiple human objects are segmented and their global motions are tracked in 3D using ellipsoid human shape models and estimates the modes (e.g., walking, running, standing) of the locomotion and 3D body postures by making inference in a prior locomotion model.
Journal ArticleDOI
Efficient moving object segmentation algorithm using background registration technique
TL;DR: An efficient moving object segmentation algorithm suitable for real-time content-based multimedia communication systems is proposed and a processing speed of 25 QCIF fps can be achieved on a personal computer with a 450-MHz Pentium III processor.
Journal ArticleDOI
Fast and automatic video object segmentation and tracking for content-based applications
Changick Kim,Jenq-Neng Hwang +1 more
TL;DR: A novel algorithm for segmentation of moving objects in video sequences and extraction of video object planes (VOPs) based on connected components analysis and smoothness of VO displacement in successive frames is proposed.
Journal ArticleDOI
Fast occluded object tracking by a robust appearance filter
TL;DR: A new method for object tracking in image sequences using template matching that is computationally fast enough to track objects in real time and able to handle abrupt changes of lighting conditions.
Book ChapterDOI
Fusion of Multiple Tracking Algorithms for Robust People Tracking
TL;DR: This paper shows how the output of a number of detection and tracking algorithms can be fused to achieve robust tracking of people in an indoor environment.