Zobrazeno 1 - 10
of 38
pro vyhledávání: '"Niels Haering"'
Publikováno v:
International Journal of Pattern Recognition and Artificial Intelligence. 24:531-555
This paper proposes a new solution to geo-register the nearly feature-less maritime video feeds. We detect the horizon using sizable or uniformly moving vessels, and estimate the vertical apex using water reflections of the street lamps. The computed
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a92bf1349dbc5583324eb091e5f1a45a
https://doi.org/10.1142/s0218001410008093
https://doi.org/10.1142/s0218001410008093
Publikováno v:
Machine Vision and Applications. 19:279-290
Over the past 10 years, computer vision research has matured significantly. Although some of the core problems, such as object recognition and shape estimation are far from solved, many applications have made considerable progress. Video Surveillance
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::68e191604f26db827709016fff665b21
https://doi.org/10.1007/s00138-008-0152-0
https://doi.org/10.1007/s00138-008-0152-0
Autor:
Niels Haering, Niels da Vitoria Lobo
Traditionally, scientific fields have defined boundaries, and scientists work on research problems within those boundaries. However, from time to time those boundaries get shifted or blurred to evolve new fields. For instance, the original goal of co
Publikováno v:
IEEE Transactions on Circuits and Systems for Video Technology. 10:857-868
We propose a three-level video-event detection methodology and apply it to animal-hunt detection in wildlife documentaries. The first level extracts color, texture, and motion features, and detects shot boundaries and moving object blobs. The mid-lev
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6b72985d5026f7c4d578cbfaacfbd0e6
https://doi.org/10.1109/76.867923
https://doi.org/10.1109/76.867923
Autor:
Niels Haering, Niels da Vitoria Lobo
Publikováno v:
Computer Vision and Image Understanding. 75:133-149
We compare features and classification methods to locate deciduous trees in images. From this comparison we conclude that a back-propagation neural network achieves better classification results than the other classifiers we tested. Our analysis of t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9d1a99304324f59471b3b229a48c8f54
https://doi.org/10.1006/cviu.1999.0769
https://doi.org/10.1006/cviu.1999.0769
Publikováno v:
COM.Geo
With more and more live sensors being added to geospatial applications, huge amount of sensor data are generated and saved in spatial database. Managing and mining these large-scale ever-changing data becomes new challenges for geospatial studies. In
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8c9d4f55cf8d69ee7bb2ed5b129e0841
https://doi.org/10.1145/2345316.2345339
https://doi.org/10.1145/2345316.2345339
Autor:
Peter L. Venetianer, Zeeshan Rasheed, Tae Eun Choe, Zhong Zhang, Andrew W. Scanlon, Li Yu, Himaanshu Gupta, Kiran Gunda, Asaad Hakeem, Atul Kanaujia, Niels Haering
Publikováno v:
Studies in Computational Intelligence ISBN: 9783642285974
Video Analytics for Business Intelligence
Video Analytics for Business Intelligence
This chapter focuses on various algorithms and techniques in video analytics that can be applied to the business intelligence domain. The goal is to provide the reader with an overview of the state of the art approaches in the field of video analytic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fe3830cd33e56e9a59513dc567f282f3
https://doi.org/10.1007/978-3-642-28598-1_10
https://doi.org/10.1007/978-3-642-28598-1_10
Autor:
Ping Wang, James Magahern, Emily Hartley, Niels Haering, Philip Lee, Kobus Barnard, Atul Kanaujia, Luca Del Pero
Publikováno v:
ACM Multimedia
We present a method for automatically aligning words to image regions that integrates specific object classifiers (e.g., "car" detectors) with weak models based on appearance features. Previous strategies have largely focused on the latter, and thus
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4b5a6beaeca73a23c39b145c11bcb567
https://doi.org/10.1145/2072298.2071951
https://doi.org/10.1145/2072298.2071951
Publikováno v:
ICCV Workshops
We present a distributed framework of understanding, indexing, and searching complex events from large amounts of surveillance video content. Video events and relationships between scene entities are represented by Spatio-Temporal And-Or Graphs (ST-A
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::442a3690b113c53684e08d8bec83b6bb
https://doi.org/10.1109/iccvw.2011.6130489
https://doi.org/10.1109/iccvw.2011.6130489
Publikováno v:
ICCV Workshops
We propose a general framework for multiple target tracking across multiple cameras using max-flow networks. The framework integrates target detection, tracking, and classification from each camera and obtains the cross-camera trajectory of each targ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::885048a63a61faee015385397111e84c
https://doi.org/10.1109/iccvw.2011.6130474
https://doi.org/10.1109/iccvw.2011.6130474