Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Eyasu Zemene"'
Publikováno v:
IET Computer Vision, Vol 10, Iss 4, Pp 289-298 (2016)
Multi‐object tracking is an interesting but challenging task in the field of computer vision. Most previous works based on data association techniques merely take into account the relationship between detection responses in a locally limited tempor
Externí odkaz:
https://doaj.org/article/0269b27a62ab4d5eb1e69a83d9d62134
Publikováno v:
International Journal of Computer Vision. 127:1303-1320
In this paper, a unified three-layer hierarchical approach for solving tracking problem in a multiple non-overlapping cameras setting is proposed. Given a video and a set of detections (obtained by any person detector), we first solve within-camera t
Akademický článek
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Publikováno v:
ICCV Workshops
Following recent technological advances there is a growing interest in building non-intrusive methods that help us communicate with computing devices. In this regard, accurate information from eye is a promising input medium between a user and comput
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::715911b7375759ed2dfc66bffe97d4e5
Autor:
Yonatan Tariku Tesfaye, Mubarak Shah, Eyasu Zemene, Haroon Idrees, Marcello Pelillo, Andrea Prati
This paper presents a new approach for the challenging problem of geo-locating an image using image matching in a structured database of city-wide reference images with known GPS coordinates. We cast the geo-localization as a clustering problem on lo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fd9b2a59858a7c03b3c554df43e265eb
Image segmentation has come a long way since the early days of computer vision, and still remains a challenging task. Modern variations of the classical (purely bottom-up) approach, involve, e.g., some form of user assistance (interactive segmentatio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::201b60665d9a686d689310e55b013c2a
Autor:
Eyasu Zemene Mequanint, Marcello Pelillo, Marco Cristani, Vittorio Murino, Hayley Hung, Sebastiano Vascon
Detecting groups is becoming of relevant interest as an important step for scene (and especially activity) understanding. Differently from what is commonly assumed in the computer vision community, different types of groups do exist, and among these,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d7726e3d5e5cbfb9e0b0766d8459a43e
Autor:
Eyasu Zemene, Marcello Pelillo
Publikováno v:
Computer Vision – ECCV 2016 ISBN: 9783319464831
ECCV (8)
ECCV (8)
We propose a new approach to interactive image segmentation based on some properties of a family of quadratic optimization problems related to dominant sets, a well-known graph-theoretic notion of a cluster which generalizes the concept of a maximal
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e8d86b9c54df716db18688c638952692
https://doi.org/10.1007/978-3-319-46484-8_17
https://doi.org/10.1007/978-3-319-46484-8_17
Multi-object tracking is an interesting but challenging task in the field of computer vision. Most previous works based on data association techniques merely take into account the relationship between detection responses in a locally limited temporal
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1491cca288e74bdf6c1ced9d5aede0f7
http://hdl.handle.net/10278/3675320
http://hdl.handle.net/10278/3675320
Publikováno v:
ICPR
We present a unified approach for simultaneous clustering and outlier detection in data. We utilize some properties of a family of quadratic optimization problems related to dominant sets, a well-known graph-theoretic notion of a cluster which genera
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fe2567586e062c42abd9cf4153fc70c8
http://hdl.handle.net/10278/3675324
http://hdl.handle.net/10278/3675324