DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Kweon, In So | - |
dc.contributor.advisor | 권인소 | - |
dc.contributor.author | Shin, Ukcheol | - |
dc.date.accessioned | 2021-05-11T19:33:24Z | - |
dc.date.available | 2021-05-11T19:33:24Z | - |
dc.date.issued | 2019 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=875338&flag=dissertation | en_US |
dc.identifier.uri | http://hdl.handle.net/10203/283044 | - |
dc.description | 학위논문(석사) - 한국과학기술원 : 전기및전자공학부, 2019.8,[v, 42 p. :] | - |
dc.description.abstract | In this thesis, we propose a noise-aware exposure control algorithm for robust robot vision. Our method aims to capture the best-exposed image which can boost the performance of various computer vision and robotics tasks. For this purpose, we carefully design an image quality metric which captures complementary quality attributes and ensures light-weight computation. Specifically, our metric consists of a combination of image gradient, entropy, and noise metrics to capture the appreciate property of an image. The synergy of these measures allows preserving sharp edge and rich texture in the image while maintaining a low noise level. Using this novel metric, we propose a real-time and fully automatic exposure and gain control technique based on the Nelder-Mead(NM) Simplex method. Also, we proposed a Modifed NM method that can react fastly and robustly to the luminance change of dynamic environment. To illustrate the effectiveness of our technique, a large set of experimental results, including feature matching, pose estimation, object detection, disparity estimation, and real-world experiments, demonstrates higher qualitative and quantitative performances when compared with conventional approaches. | - |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | Camera exposure control▼aauto exposure control▼arobot vision▼afast noise estimation▼aimage quality assessment metric | - |
dc.subject | 카메라 노출 제어▼a자동 노출 제어▼a로봇 비전▼a빠른 노이즈 추정▼a이미지 품질 평가 지표 | - |
dc.title | Noise-aware camera exposure control for robust robot vision | - |
dc.title.alternative | 강인한 로봇 비전을 위한 노이즈 인식 기반 카메라 노출 제어 방법 | - |
dc.type | Thesis(Master) | - |
dc.identifier.CNRN | 325007 | - |
dc.description.department | 한국과학기술원 :전기및전자공학부, | - |
dc.contributor.alternativeauthor | 신욱철 | - |
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