Cover Image

A Robust Method for Hand Tracking Using Mean-shift Algorithm and Kalman Filter in Stereo Color Image Sequences

Main Authors: Mahmoud Elmezain, Ayoub Al-Hamadi, Robert Niese, Bernd Michaelis
Format: Article eJournal
Bahasa: eng
Terbitan: , 2009
Subjects:
Computer Vision and Image Analysis
Object Tracking
Gesture Recognition
Online Access: https://zenodo.org/record/1073597
ctrlnum 1073597
fullrecord <?xml version="1.0"?> <dc schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><creator>Mahmoud Elmezain</creator><creator>Ayoub Al-Hamadi</creator><creator>Robert Niese</creator><creator>Bernd Michaelis</creator><date>2009-11-25</date><description>Real-time hand tracking is a challenging task in many computer vision applications such as gesture recognition. This paper proposes a robust method for hand tracking in a complex environment using Mean-shift analysis and Kalman filter in conjunction with 3D depth map. The depth information solve the overlapping problem between hands and face, which is obtained by passive stereo measuring based on cross correlation and the known calibration data of the cameras. Mean-shift analysis uses the gradient of Bhattacharyya coefficient as a similarity function to derive the candidate of the hand that is most similar to a given hand target model. And then, Kalman filter is used to estimate the position of the hand target. The results of hand tracking, tested on various video sequences, are robust to changes in shape as well as partial occlusion.</description><identifier>https://zenodo.org/record/1073597</identifier><identifier>10.5281/zenodo.1073597</identifier><identifier>oai:zenodo.org:1073597</identifier><language>eng</language><relation>doi:10.5281/zenodo.1073596</relation><relation>url:https://zenodo.org/communities/waset</relation><rights>info:eu-repo/semantics/openAccess</rights><rights>https://creativecommons.org/licenses/by/4.0/legalcode</rights><subject>Computer Vision and Image Analysis</subject><subject>Object Tracking</subject><subject>Gesture Recognition.</subject><title>A Robust Method for Hand Tracking Using Mean-shift Algorithm and Kalman Filter in Stereo Color Image Sequences</title><type>Journal:Article</type><type>Journal:Article</type><recordID>1073597</recordID></dc>
language eng
format Journal:Article
Journal
Journal:eJournal
author Mahmoud Elmezain
Ayoub Al-Hamadi
Robert Niese
Bernd Michaelis
title A Robust Method for Hand Tracking Using Mean-shift Algorithm and Kalman Filter in Stereo Color Image Sequences
publishDate 2009
topic Computer Vision and Image Analysis
Object Tracking
Gesture Recognition
url https://zenodo.org/record/1073597
contents Real-time hand tracking is a challenging task in many computer vision applications such as gesture recognition. This paper proposes a robust method for hand tracking in a complex environment using Mean-shift analysis and Kalman filter in conjunction with 3D depth map. The depth information solve the overlapping problem between hands and face, which is obtained by passive stereo measuring based on cross correlation and the known calibration data of the cameras. Mean-shift analysis uses the gradient of Bhattacharyya coefficient as a similarity function to derive the candidate of the hand that is most similar to a given hand target model. And then, Kalman filter is used to estimate the position of the hand target. The results of hand tracking, tested on various video sequences, are robust to changes in shape as well as partial occlusion.
id IOS17403.1073597
institution Universitas PGRI Palembang
institution_id 189
institution_type library:university
library
library Perpustakaan Universitas PGRI Palembang
library_id 587
collection Marga Life in South Sumatra in the Past: Puyang Concept Sacrificed and Demythosized
repository_id 17403
city KOTA PALEMBANG
province SUMATERA SELATAN
repoId IOS17403
first_indexed 2022-07-26T03:46:50Z
last_indexed 2022-07-26T03:46:50Z
recordtype dc
merged_child_boolean 1
_version_ 1739481305795526656
score 17.538404

Lihat Juga