{"type":"ScholarlyArticle","title":"Active Recurrence of Lighting Condition for Fine-Grained Change Detection","authors":[{"name":"Qian Zhang","slug":"qian-zhang","given":"Qian","family":"Zhang","affiliation":"School of Computer Science and Technology , Tianjin University , China; Key Research Center for Surface Monitoring and Analysis of Cultural Relics , SACH , China"},{"name":"Wei Feng","slug":"wei-feng","given":"Wei","family":"Feng","affiliation":"School of Computer Science and Technology , Tianjin University , China; Key Research Center for Surface Monitoring and Analysis of Cultural Relics , SACH , China"},{"name":"Liang Wan","slug":"liang-wan","given":"Liang","family":"Wan","affiliation":"Key Research Center for Surface Monitoring and Analysis of Cultural Relics , SACH , China; School of Computer Software , Tianjin University , China"},{"name":"Fei-Peng Tian","slug":"fei-peng-tian","given":"Fei-Peng","family":"Tian","affiliation":"School of Computer Science and Technology , Tianjin University , China; Key Research Center for Surface Monitoring and Analysis of Cultural Relics , SACH , China"},{"name":"Ping Tan","slug":"ping-tan","given":"Ping","family":"Tan","affiliation":"School of Computing Science , Simon Fraser University , Canada"}],"abstract":"This paper addresses active lighting recurrence (ALR), a new problem that actively relocalizes a light source to physically reproduce the lighting condition for a same scene from single reference image. ALR is of great importance for fine-grained visual monitoring and change detection, because some phenomena or minute changes can only be clearly observed under particular lighting conditions. Hence, effective ALR should be able to online navigate a light source toward the target pose, which is challenging due to the complexity and diversity of real-world lighting \\& imaging processes. We propose to use the simple parallel lighting as an analogy model and based on Lambertian law to compose an instant navigation ball for this purpose. We theoretically prove the feasibility of this ALR strategy for realistic near point light sources and its invariance to the ambiguity of normal \\& lighting decomposition. Extensive quantitative experiments and challenging real-world tasks on fine-grained change monitoring of cultural heritages verify the effectiveness of our approach. We also validate its generality to non-Lambertian scenes.","doi":"10.24963/ijcai.2018/690","url":"https://ijcai.org/proceedings/2018/690","pdf":"https://ijcai.org/proceedings/2018/0690.pdf","markdown":"https://ijcai.org/proceedings/2018/690.md","bibtex":"https://ijcai.org/proceedings/2018/bibtex/690","volume":{"slug":"2018","title":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2018","url":"https://ijcai.org/proceedings/2018/","year":2018,"location":"Stockholm","dates":"13-19 July 2018","editors":"Jérôme Lang","isbn":"978-0-9992411-2-7","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2018"},"section":"Robotics","track":"Main track","number":690,"pages":{"first":4972,"last":4978},"keywords":["Computer Vision: Computational Photography, Photometry, Shape from X","Computer Vision: Computer Vision","Robotics: Robotics and Vision"],"videos":[],"references":[{"position":1,"raw":"[Debevec et al., 2000] P. 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