Modified Mean-Shift for head tracking

2011 ◽  
Author(s):  
Daeha Lee ◽  
Jaehong Kim ◽  
JooChan Sohn
Keyword(s):  
Mean Shift ◽  
Head Tracking

scholarly journals TIR-MS: Thermal Infrared Mean-Shift for Robust Pedestrian Head Tracking in Dynamic Target and Background Variations

2019 ◽  
Vol 9 (15) ◽  
pp. 3015 ◽  
Author(s):  
Sungmin Yun ◽  
Sungho Kim
Keyword(s):  
Probability Distributions ◽  
Mean Shift ◽  
Thermal Infrared ◽  
Temperature Data ◽  
Seasonal Effect ◽  
Head Tracking ◽  
Pedestrian Tracking ◽  
Local Maxima ◽  
Dynamic Target ◽  
Feature Values

Thermal infrared (TIR) pedestrian tracking is one of the major issues in computer vision. Mean-shift is a powerful and versatile non-parametric iterative algorithm for finding local maxima in probability distributions. In existing infrared data, and mean-shift-based tracking is generally based on the brightness feature values. Unfortunately, the brightness is distorted by the target and background variations. This paper proposes a novel pedestrian tracking algorithm, thermal infrared mean-shift (TIR-MS), by introducing radiometric temperature data in mean-shift tracking. The thermal brightness image (eight-bits) was distorted by the automatic contrast enhancement of the scene such as hot objects in the background. On the other hand, the temperature data was unaffected directly by the background change, except for variations by the seasonal effect, which is more stable than the brightness. The experimental results showed that the TIR-MS outperformed the original mean-shift-based brightness when tracking a pedestrian head with successive background variations.

New AAC Access Strategy for Gesture Tracking: A Technical Note

2012 ◽  
Vol 21 (1) ◽  
pp. 11-16 ◽  
Author(s):  
Susan Fager ◽  
Tom Jakobs ◽  
David Beukelman ◽  
Tricia Ternus ◽  
Haylee Schley
Keyword(s):  
Augmentative And Alternative Communication ◽  
Technical Note ◽  
Head Tracking ◽  
Alternative Communication ◽  
Access Methods ◽  
Cord Injury ◽  
Physical Limitations ◽  
Gesture Tracking ◽  
Communication Needs ◽  
Tracking Device

Abstract This article summarizes the design and evaluation of a new augmentative and alternative communication (AAC) interface strategy for people with complex communication needs and severe physical limitations. This strategy combines typing, gesture recognition, and word prediction to input text into AAC software using touchscreen or head movement tracking access methods. Eight individuals with movement limitations due to spinal cord injury, amyotrophic lateral sclerosis, polio, and Guillain Barre syndrome participated in the evaluation of the prototype technology using a head-tracking device. Fourteen typical individuals participated in the evaluation of the prototype using a touchscreen.

Head tracking latency in virtual environments: Psychophysics and a model

2003 ◽  
Author(s):  
Bernard D. Adelstein ◽  
Thomas G. Lee ◽  
Stephen R. Ellis
Keyword(s):  
Virtual Environments ◽  
Head Tracking

Head Tracking: A Comprehensive Review

2020 ◽  
Vol 13 (2) ◽  
Author(s):  
Saket Kumar ◽  
Rajesh Mehra
Keyword(s):  
Head Tracking ◽  
Comprehensive Review

Mean-Shift tracking algorithm based on FCM

2010 ◽  
Vol 29 (12) ◽  
pp. 3332-3335 ◽  
Author(s):  
Cun-wei TIAN ◽  
Guang-ying GE ◽  
Zhe SHEN
Keyword(s):  
Mean Shift ◽  
Tracking Algorithm

Color image segmentation based on mean shift and multi-feature fusion

2009 ◽  
Vol 29 (8) ◽  
pp. 2074-2076
Author(s):  
Hua LI ◽  
Ming-xin ZHANG ◽  
Jing-long ZHENG
Keyword(s):  
Image Segmentation ◽  
Feature Fusion ◽  
Color Image ◽  
Mean Shift ◽  
Color Image Segmentation

Algorithm of target tracking based on Mean-Shift with adaptive bandwidth of kernel function

2009 ◽  
Vol 29 (6) ◽  
pp. 1680-1682
Author(s):  
Chang-tao CHEN ◽  
Qin ZHU ◽  
Sheng-yi ZHOU ◽  
Jia-ming ZHANG
Keyword(s):  
Target Tracking ◽  
Kernel Function ◽  
Mean Shift ◽  
Adaptive Bandwidth
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