完整後設資料紀錄
DC 欄位語言
dc.contributor.authorWang, Tsaipeien_US
dc.contributor.authorChang, Chia-Weien_US
dc.contributor.authorWu, Yu-Shanen_US
dc.date.accessioned2018-08-21T05:57:14Z-
dc.date.available2018-08-21T05:57:14Z-
dc.date.issued2017-01-01en_US
dc.identifier.urihttp://hdl.handle.net/11536/147202-
dc.description.abstractThis paper describes a new algorithm for detecting people using a single downward-viewing fisheye camera. People detection from images taken with projective cameras has been studied extensively in recent years. On the other hand, researches on people detection from fisheye camera images are very limited, and existing techniques are either designed for very simplistic and uncluttered environments, or are very time-consuming. Given that fisheye cameras have a number of advantages in application such as people counting and visual surveillance, including less occlusion among peoples and larger views, the objective here is to propose a new technique of people counting using fisheye cameras that is both practical to realistic environments and efficient enough for real-time applications. The main innovation of our method is to take advantage of fisheye geometries to estimate the expected sizes of people as functions of image locations. An adaptive set of elliptic templates are pre computed to expedite processing. Given the different appearances of people at different distances to the image center, a set of support vector machines (SVMs) are used to classify different templates as people or not. We also describe a tracking algorithm for people counting and tracking in indoor environments.en_US
dc.language.isoen_USen_US
dc.subjectPeople Detectionen_US
dc.subjectFisheye Camerasen_US
dc.subjectOmnivision Camerasen_US
dc.titleTEMPLATE-BASED PEOPLE DETECTION USING A SINGLE DOWNWARD-VIEWING FISHEYE CAMERAen_US
dc.typeProceedings Paperen_US
dc.identifier.journal2017 INTERNATIONAL SYMPOSIUM ON INTELLIGENT SIGNAL PROCESSING AND COMMUNICATION SYSTEMS (ISPACS 2017)en_US
dc.citation.spage719en_US
dc.citation.epage723en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000428142000136en_US
顯示於類別:會議論文