Adaptive homochromous disturbance elimination and feature selection based mean-shift vehicle tracking method

Jie Ding; Bo Lei; Pu Hong; Chensheng Wang

doi:10.1117/12.904669

Adaptive homochromous disturbance elimination and feature selection based mean-shift vehicle tracking method

Jie Ding^*, Bo Lei, Pu Hong, Chensheng Wang

^*Corresponding author for this work

School of Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

1 Citation (Scopus)

Abstract

This paper introduces a novel method to adaptively diminish the effects of disturbance in the airborne camera shooting traffic video. Based on the moving vector of the tracked vehicle, a search area in the next frame is predicted, which is the area of interest (AOI) to the mean-shift method. Background color estimation is performed according to the previous tracking, which is used to judge whether there is possible disturbance in the predicted search area in the next frame. Without disturbance, the difference image of vehicle and background could be used as input features to the mean-shift algorithm; with disturbance, the histogram of colors in the predict area is calculated to find the most and second disturbing color. Experiments proved this method could diminish or eliminate the effects of homochromous disturbance and lead to more precise and more robust tracking.

Original language	English
Title of host publication	2011 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology
Pages	1-12
Number of pages	12
Volume	8200
DOIs	https://doi.org/10.1117/12.904669
Publication status	Published - 2011
Event	2011 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology - Beijing, China Duration: 6 Nov 2011 → 9 Nov 2011

Other

Other	2011 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology
Country/Territory	China
City	Beijing
Period	6/11/11 → 9/11/11

Keywords

Adaptive feature selection
Airborne video
Homochromous disturbance
Mean-shift
Vehicle tracking

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10.1117/12.904669

Cite this

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title = "Adaptive homochromous disturbance elimination and feature selection based mean-shift vehicle tracking method",

abstract = "This paper introduces a novel method to adaptively diminish the effects of disturbance in the airborne camera shooting traffic video. Based on the moving vector of the tracked vehicle, a search area in the next frame is predicted, which is the area of interest (AOI) to the mean-shift method. Background color estimation is performed according to the previous tracking, which is used to judge whether there is possible disturbance in the predicted search area in the next frame. Without disturbance, the difference image of vehicle and background could be used as input features to the mean-shift algorithm; with disturbance, the histogram of colors in the predict area is calculated to find the most and second disturbing color. Experiments proved this method could diminish or eliminate the effects of homochromous disturbance and lead to more precise and more robust tracking.",

keywords = "Adaptive feature selection, Airborne video, Homochromous disturbance, Mean-shift, Vehicle tracking",

author = "Jie Ding and Bo Lei and Pu Hong and Chensheng Wang",

year = "2011",

doi = "10.1117/12.904669",

language = "English",

isbn = "9780819488411",

volume = "8200",

pages = "1--12",

booktitle = "2011 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology",

note = "2011 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology ; Conference date: 06-11-2011 Through 09-11-2011",

}

Ding, J, Lei, B, Hong, P & Wang, C 2011, Adaptive homochromous disturbance elimination and feature selection based mean-shift vehicle tracking method. in 2011 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology. vol. 8200, 820005, pp. 1-12, 2011 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology, Beijing, China, 6/11/11. https://doi.org/10.1117/12.904669

Adaptive homochromous disturbance elimination and feature selection based mean-shift vehicle tracking method. / Ding, Jie; Lei, Bo; Hong, Pu et al.
2011 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology. Vol. 8200 2011. p. 1-12 820005.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

TY - GEN

T1 - Adaptive homochromous disturbance elimination and feature selection based mean-shift vehicle tracking method

AU - Ding, Jie

AU - Lei, Bo

AU - Hong, Pu

AU - Wang, Chensheng

PY - 2011

Y1 - 2011

N2 - This paper introduces a novel method to adaptively diminish the effects of disturbance in the airborne camera shooting traffic video. Based on the moving vector of the tracked vehicle, a search area in the next frame is predicted, which is the area of interest (AOI) to the mean-shift method. Background color estimation is performed according to the previous tracking, which is used to judge whether there is possible disturbance in the predicted search area in the next frame. Without disturbance, the difference image of vehicle and background could be used as input features to the mean-shift algorithm; with disturbance, the histogram of colors in the predict area is calculated to find the most and second disturbing color. Experiments proved this method could diminish or eliminate the effects of homochromous disturbance and lead to more precise and more robust tracking.

AB - This paper introduces a novel method to adaptively diminish the effects of disturbance in the airborne camera shooting traffic video. Based on the moving vector of the tracked vehicle, a search area in the next frame is predicted, which is the area of interest (AOI) to the mean-shift method. Background color estimation is performed according to the previous tracking, which is used to judge whether there is possible disturbance in the predicted search area in the next frame. Without disturbance, the difference image of vehicle and background could be used as input features to the mean-shift algorithm; with disturbance, the histogram of colors in the predict area is calculated to find the most and second disturbing color. Experiments proved this method could diminish or eliminate the effects of homochromous disturbance and lead to more precise and more robust tracking.

KW - Adaptive feature selection

KW - Airborne video

KW - Homochromous disturbance

KW - Mean-shift

KW - Vehicle tracking

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DO - 10.1117/12.904669

M3 - Conference proceeding contribution

AN - SCOPUS:83655164454

SN - 9780819488411

VL - 8200

SP - 1

EP - 12

BT - 2011 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology

T2 - 2011 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology

Y2 - 6 November 2011 through 9 November 2011

ER -

Adaptive homochromous disturbance elimination and feature selection based mean-shift vehicle tracking method

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