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Title:

Precise Segmentation and Position Estimation of Pedestrians By the Combination of the HOG Classifier and the S-T MRF Model

Accession Number:

01372466

Record Type:

Component

Abstract:

This paper presents a general algorithm for pedestrian detection by on-board monocular camera which can be applied to cameras of various view ranges. Under the assumption that motion of background can be nearly approximated as a linear function, the Spatio-Temporal MRF (S-T MRF) model segments foreground objects. Those foreground objects contain both pedestrian and non-pedestrian urban objects, verification by a cascaded classifier is conducted. However, segmentation result sometime contains error such as shrunk or inflated Region of Interest (ROI). The authors improved their system by implementing two types of feedback algorithm for ROI correction using the Kalman filter and by combining the results of motion classifier and HOG classifier. They confirmed that those ROI Corrections help the system decrease the false negative rate and extract highly accurate pedestrian trajectory. They expect that the trajectory could be used as a useful source for measuring the possibility of collision with pedestrian.

Supplemental Notes:

This paper was sponsored by TRB committee ANF10 Pedestrians

Monograph Accession #:

01362476

Report/Paper Numbers:

12-4526

Language:

English

Corporate Authors:

Transportation Research Board

500 Fifth Street, NW
Washington, DC 20001 United States

Authors:

Kim, HyungKwan
Shibayama, Yuuki
Kamijo, Shunsuke

Pagination:

16p

Publication Date:

2012

Conference:

Transportation Research Board 91st Annual Meeting

Location: Washington DC, United States
Date: 2012-1-22 to 2012-1-26
Sponsors: Transportation Research Board

Media Type:

Digital/other

Features:

Figures; References; Tables

Subject Areas:

Highways; Pedestrians and Bicyclists; Safety and Human Factors; Vehicles and Equipment; I91: Vehicle Design and Safety

Source Data:

Transportation Research Board Annual Meeting 2012 Paper #12-4526

Files:

TRIS, TRB

Created Date:

Feb 8 2012 5:25PM