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Face detection using AdaBoost and template matching : AdaBoost와 템플릿 매칭을 이용한 얼굴 검출
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.advisor | 강명주 | - |
| dc.contributor.author | 방미림 | - |
| dc.date.accessioned | 2017-07-19T08:59:21Z | - |
| dc.date.available | 2017-07-19T08:59:21Z | - |
| dc.date.issued | 2014-02 | - |
| dc.identifier.other | 000000017749 | - |
| dc.identifier.uri | https://hdl.handle.net/10371/131477 | - |
| dc.description | 학위논문 (석사)-- 서울대학교 대학원 : 수리과학부, 2014. 2. 강명주. | - |
| dc.description.abstract | This work contains the existing face detection method on gray-scale static image. Discrete-AdaBoost algorithm which is proposed by Viola-Jones is one of the typical real-time face detection methods with superior speed and performance. Then Maio and Maltoni's paper is reviewed, and it suggested the template matching algorithm which enhances the face detection rate.
The Viola-Jones face detector contains three main ideas that make it possible to build a successful face detector that can run in real time: the integral image, classifier learning with AdaBoost, and the attentional cascade structure. Maio and Maltoni's method approximately detects the image positions where the probability of finding a face is high | - |
| dc.description.abstract | next, the location accuracy of the candidate faces is improved and their existence is verified. | - |
| dc.description.tableofcontents | Abstract i
1 Introduction 1 1.1 Previous work . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 2 The Viola-Jones algorithm 4 2.1 The integral image . . . . . . . . . . . . . . . . . . . . . . . . 4 2.2 AdaBoost learning . . . . . . . . . . . . . . . . . . . . . . . . 5 2.3 The attentional cascade structure . . . . . . . . . . . . . . . . 8 2.4 Experimental results . . . . . . . . . . . . . . . . . . . . . . . 10 3 The Maio and Maltoni algorithm 11 3.1 Directional image . . . . . . . . . . . . . . . . . . . . . . . . . 11 3.2 Approximate location . . . . . . . . . . . . . . . . . . . . . . . 11 3.3 Fine location and face verification . . . . . . . . . . . . . . . . 15 3.4 Combining AL and FLFV . . . . . . . . . . . . . . . . . . . . 18 3.5 Experimental results . . . . . . . . . . . . . . . . . . . . . . . 19 4 Conclusion 23 Abstract (in Korean) 27 | - |
| dc.format | application/pdf | - |
| dc.format.extent | 6553480 bytes | - |
| dc.format.medium | application/pdf | - |
| dc.language.iso | en | - |
| dc.publisher | 서울대학교 대학원 | - |
| dc.subject | Face detection | - |
| dc.subject | Viola-Jones | - |
| dc.subject | Template Matching | - |
| dc.subject | AdaBoost | - |
| dc.subject | Directional image | - |
| dc.subject | Generalized Hough transform | - |
| dc.subject.ddc | 510 | - |
| dc.title | Face detection using AdaBoost and template matching | - |
| dc.title.alternative | AdaBoost와 템플릿 매칭을 이용한 얼굴 검출 | - |
| dc.type | Thesis | - |
| dc.description.degree | Master | - |
| dc.citation.pages | iv,27 | - |
| dc.contributor.affiliation | 자연과학대학 수리과학부 | - |
| dc.date.awarded | 2014-02 | - |
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