Transcript Recently Meanshift/Camshift Tracking Research

Recent Meanshift/Camshift
Tracking Research
outline


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Introduction
Improvement and combination
Individual introduction
conclusion
Introduction
 Reference collection
 More related work
 Select from 2007 to now , all papers about
meanshift/camshift on IEEE
Improvement and combination
 Improvement:
 (1) An Improved Mean Shift Algorithm For Object
Tracking
 (2) The application of improved HSV color space
model in image processing
 (3) New Method of Object Tracking under Complex
 Circumstance
Improvement and combination
 combination:
 (1) Vehicle Tracking Method Using Background
Subtraction and MeanShift Algorithm
 (2) Video Facial Feature Tracking with Enhanced ASM
and Predicted Meanshift
(3) A MeanShift-Particle Fusion Tracking Algorithm
Based on SIFT*
 (4) A Real Time Object Tracking System for Contrast
 Media Injection
Improvement and combination
 combination:
 (5) A Robust Combined Algorithim of Object Tracking
Based on Moving Object Detection
 (6) Anti-occlusion Tracking Algorithm Based on
LSSVM Prediction and Kalman-MeanShift
 (7) Efficient visual servoing with the ABCshift tracking
algorithm
 (8) Object Tracking Algorithm Based on Meanshift
Algorithm Combining with Motion Vector analysis
An Improved Mean Shift Algorithm
For Object Tracking
 簡體中文
 方法：靠近目標中心的像素點增加權重
The application of improved HSV
color space model in image
processing
 HSVSHSV(shift-HSV)
New Method of Object Tracking
under Complex
Circumstance
 Area weighted centroid shifting algorithm
Vehicle Tracking Method Using
Background Subtraction and
MeanShift Algorithm
Video Facial Feature Tracking with
Enhanced ASM and Predicted
Meanshift
 Active Shape Model (ASM)
A MeanShift-Particle Fusion Tracking
Algorithm Based on SIFT*
A Real Time Object Tracking System
for Contrast
Media Injection
 A. MeanShift algorithm
B. Contour detection

A Robust Combined Algorithim of
Object Tracking Based on Moving
Object Detection
 MOVING OBJECT DETECTION

Anti-occlusion Tracking Algorithm
Based on LSSVM Prediction and
Kalman-MeanShift
 LSSVM = least square SVM
Efficient visual servoing with the
ABCshift tracking algorithm
 ABCshift = Apapting Background Camshift
Object Tracking Algorithm Based on
Meanshift Algorithm Combining with
Motion Vector analysis
Conclusion
 增加了不少文章的reference
 對機器人追蹤有現成的進階做法能參考