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dc.contributor.authorWang, Tsaipeien_US
dc.contributor.authorHsieh, Yun-Yien_US
dc.contributor.authorWong, Fong-Wenen_US
dc.contributor.authorChen, Yi-Fuen_US
dc.date.accessioned2020-05-05T00:02:00Z-
dc.date.available2020-05-05T00:02:00Z-
dc.date.issued2019-01-01en_US
dc.identifier.isbn978-1-7281-4666-9en_US
dc.identifier.issn2376-6816en_US
dc.identifier.urihttp://hdl.handle.net/11536/154059-
dc.description.abstractPeople detection is a core problem in many applications, such as those related to visual surveillance and behavior analysis. In recent years, we have seen dramatic improvements of people detection techniques based on deep neural networks. However, most of the techniques are developed for projective cameras where people mostly appear upright in the images. On the other hand, images taken with top-view fisheye cameras, another major modality used in visual surveillance, have received little attention. In this paper, we present a study on extending the well-known Mask-RCNN people detection algorithm to such images.en_US
dc.language.isoen_USen_US
dc.subjectpeople detectionen_US
dc.subjecthuman detectionen_US
dc.subjectfisheye camerasen_US
dc.subjectomnivision camerasen_US
dc.subjecttransfer learningen_US
dc.titleMask-RCNN Based People Detection Using A Top-View Fisheye Cameraen_US
dc.typeProceedings Paperen_US
dc.identifier.journal2019 INTERNATIONAL CONFERENCE ON TECHNOLOGIES AND APPLICATIONS OF ARTIFICIAL INTELLIGENCE (TAAI)en_US
dc.citation.spage0en_US
dc.citation.epage0en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000524126200046en_US
dc.citation.woscount0en_US
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