Dynamic region-of-interest acquisition and face tracking for intelligent surveillance system
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Y.-O. | - |
dc.contributor.author | Kim, S. | - |
dc.contributor.author | Park, C.-W. | - |
dc.contributor.author | Sung, H.-G. | - |
dc.contributor.author | Paik, J. | - |
dc.date.accessioned | 2022-04-11T12:40:08Z | - |
dc.date.available | 2022-04-11T12:40:08Z | - |
dc.date.issued | 2004-01 | - |
dc.identifier.issn | 0277-786X | - |
dc.identifier.uri | https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/56279 | - |
dc.description.abstract | Recently, surveillance systems gain more attraction than simple CCTV systems, especially for complicated security environment. The major purpose of the proposed system is to monitor and track intruders. More specifically, accurate identification of each intruder is more important than simply recording what they are doing. Most existing surveillance systems simply keep recording the fixed viewing area, and some others adopt the tracking technique for wider coverage. Although panning and tilting the camera can extend the viewing area, only a few automatic zoom control techniques for acquiring the optimum ROI has been proposed. This paper describes a system for tracking multiple faces from input video sequences using facial convex hull-based facial segmentation and robust hausdorff distance. The proposed algorithm adapts skin color reference map in the YCbCr color space and hair color reference map in the RGB color space for classifying face region. Then, we obtain an initial face model with preprocessing and convex hull. For tracking, this algorithm computes displacement of the point set between frames using a robust hausdorff distance and the best possible displacement is selected. Finally, the initial face model is updated using the displacement. We provide experimental result to demonstrate the performance of the proposed tracking algorithm, which efficiently tracks rotating, and zooming faces as well as multiple faces in video sequences obtained from at CCD camera. | - |
dc.format.extent | 9 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.title | Dynamic region-of-interest acquisition and face tracking for intelligent surveillance system | - |
dc.type | Article | - |
dc.identifier.doi | 10.1117/12.527182 | - |
dc.identifier.bibliographicCitation | Proceedings of SPIE - The International Society for Optical Engineering, v.5299, pp 369 - 377 | - |
dc.description.isOpenAccess | N | - |
dc.identifier.wosid | 000222330700037 | - |
dc.identifier.scopusid | 2-s2.0-8844231714 | - |
dc.citation.endPage | 377 | - |
dc.citation.startPage | 369 | - |
dc.citation.title | Proceedings of SPIE - The International Society for Optical Engineering | - |
dc.citation.volume | 5299 | - |
dc.type.docType | Conference Paper | - |
dc.publisher.location | 미국 | - |
dc.subject.keywordAuthor | Active camera | - |
dc.subject.keywordAuthor | Convex hull | - |
dc.subject.keywordAuthor | Face segmentation | - |
dc.subject.keywordAuthor | Face tracking | - |
dc.subject.keywordAuthor | Robust hausdorff distance | - |
dc.subject.keywordPlus | Algorithms | - |
dc.subject.keywordPlus | Cameras | - |
dc.subject.keywordPlus | Charge coupled devices | - |
dc.subject.keywordPlus | Computational methods | - |
dc.subject.keywordPlus | Image segmentation | - |
dc.subject.keywordPlus | Intelligent control | - |
dc.subject.keywordPlus | Robustness (control systems) | - |
dc.subject.keywordPlus | Active cameras | - |
dc.subject.keywordPlus | Convex hull | - |
dc.subject.keywordPlus | Face segmentation | - |
dc.subject.keywordPlus | Face tracking | - |
dc.subject.keywordPlus | Robust hausdorff distance | - |
dc.subject.keywordPlus | Face recognition | - |
dc.relation.journalResearchArea | Imaging Science & Photographic Technology | - |
dc.relation.journalWebOfScienceCategory | Imaging Science & Photographic Technology | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
84, Heukseok-ro, Dongjak-gu, Seoul, Republic of Korea (06974)02-820-6194
COPYRIGHT 2019 Chung-Ang University All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.