Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Wang, Tsaipei | en_US |
dc.contributor.author | Hsieh, Yun-Yi | en_US |
dc.contributor.author | Wong, Fong-Wen | en_US |
dc.contributor.author | Chen, Yi-Fu | en_US |
dc.date.accessioned | 2020-05-05T00:02:00Z | - |
dc.date.available | 2020-05-05T00:02:00Z | - |
dc.date.issued | 2019-01-01 | en_US |
dc.identifier.isbn | 978-1-7281-4666-9 | en_US |
dc.identifier.issn | 2376-6816 | en_US |
dc.identifier.uri | http://hdl.handle.net/11536/154059 | - |
dc.description.abstract | People 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.iso | en_US | en_US |
dc.subject | people detection | en_US |
dc.subject | human detection | en_US |
dc.subject | fisheye cameras | en_US |
dc.subject | omnivision cameras | en_US |
dc.subject | transfer learning | en_US |
dc.title | Mask-RCNN Based People Detection Using A Top-View Fisheye Camera | en_US |
dc.type | Proceedings Paper | en_US |
dc.identifier.journal | 2019 INTERNATIONAL CONFERENCE ON TECHNOLOGIES AND APPLICATIONS OF ARTIFICIAL INTELLIGENCE (TAAI) | en_US |
dc.citation.spage | 0 | en_US |
dc.citation.epage | 0 | en_US |
dc.contributor.department | 資訊工程學系 | zh_TW |
dc.contributor.department | Department of Computer Science | en_US |
dc.identifier.wosnumber | WOS:000524126200046 | en_US |
dc.citation.woscount | 0 | en_US |
Appears in Collections: | Conferences Paper |