Partial person re-identification with convolutional neural network and attention model = 컨볼루셔널 신경망과 집중 모델을 이용한 부분적인 사람 재확인 시스템의 개발

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We address a partial person re-identification problem, where only a part of person is observed and full body images are presented to be matched. This partial person re-identification is more challenging problem than conventional person re-identification problem which only considers full body images of person. In order to solve this problem, we proposed end-to-end deep model which make use of convolutional neural network (CNN), ROI Pooling layer, and attention model. For evaluation for proposed model, we process CUHK03 data to make simulated data, p-CUHK03, and quantitatively evaluated proposed model.
Advisors
Yoo, Chang Dongresearcher유창동researcher
Description
한국과학기술원 :전기및전자공학부,
Publisher
한국과학기술원
Issue Date
2017
Identifier
325007
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 전기및전자공학부, 2017.2,[iii, 28 p. :]

Keywords

Partial person re-identification; Convolutional Neural Network; Attention model; ROI Pooling; p-CUHK03; 부분적인 사람 재확인; 컨볼루셔널 신경망; 집중모델; 관심영역 특징 추출; 집중 모델

URI
http://hdl.handle.net/10203/243264
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=675370&flag=dissertation
Appears in Collection
EE-Theses_Master(석사논문)
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