Multi-object tracking in video
Real-Time Imaging - Special issue on real-time digital video over multimedia
A survey of computer vision-based human motion capture
Computer Vision and Image Understanding - Modeling people toward vision-based underatanding of a person's shape, appearance, and movement
Object Oriented Motion Estimation in Color Image Sequences
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
Towards Improved Observation Models for Visual Tracking: Selective Adaptation
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Fusion of Multiple Tracking Algorithms for Robust People Tracking
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Moving Object Tracking in Video
AIPR '00 Proceedings of the 29th Applied Imagery Pattern Recognition Workshop
Moving Target Classification and Tracking from Real-time Video
WACV '98 Proceedings of the 4th IEEE Workshop on Applications of Computer Vision (WACV'98)
Using Histograms to Detect and Track Objects in Color Video
AIPR '01 Proceedings of the 30th on Applied Imagery Pattern Recognition Workshop
A Real-Time Object Tracking System Using a Color Camera
AIPR '01 Proceedings of the 30th on Applied Imagery Pattern Recognition Workshop
An Introduction to the Kalman Filter
An Introduction to the Kalman Filter
Tracking Multiple Humans in Complex Situations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Image Processing (3rd Edition)
Digital Image Processing (3rd Edition)
Fast object tracking in digital video
IEEE Transactions on Consumer Electronics
Fast occluded object tracking by a robust appearance filter
IEEE Transactions on Pattern Analysis and Machine Intelligence
Motion segmentation by multistage affine classification
IEEE Transactions on Image Processing
Fast and automatic video object segmentation and tracking for content-based applications
IEEE Transactions on Circuits and Systems for Video Technology
Efficient moving object segmentation algorithm using background registration technique
IEEE Transactions on Circuits and Systems for Video Technology
WSEAS Transactions on Computers
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part II
Human tracking: a state-of-art survey
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part II
GPU-supported object tracking using adaptive appearance models and particle swarm optimization
ICCVG'10 Proceedings of the 2010 international conference on Computer vision and graphics: Part II
Multiple object tracking using HSV color space
Proceedings of the 2011 International Conference on Communication, Computing & Security
Comparison of stochastic filtering methods for 3D tracking
Pattern Recognition
Upper body gesture recognition for human-robot interaction
HCII'11 Proceedings of the 14th international conference on Human-computer interaction: interaction techniques and environments - Volume Part II
Detection and tracking of multiple similar objects based on color-pattern
AIS'11 Proceedings of the Second international conference on Autonomous and intelligent systems
A hybrid motion and appearance prediction model for robust visual object tracking
Pattern Recognition Letters
On-line Support Vector Regression of the transition model for the Kalman filter
Image and Vision Computing
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In this paper, a new video moving object tracking method is proposed. In initialization, a moving object selected by the user is segmented and the dominant color is extracted from the segmented target. In tracking step, a motion model is constructed to set the system model of adaptive Kalman filter firstly. Then, the dominant color of the moving object in HSI color space will be used as feature to detect the moving object in the consecutive video frames. The detected result is fed back as the measurement of adaptive Kalman filter and the estimate parameters of adaptive Kalman filter are adjusted by occlusion ratio adaptively. The proposed method has the robust ability to track the moving 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 moving object, and changing the velocity of moving object suddenly. The proposed method is an efficient video object tracking algorithm.