E
Ebroul Izquierdo
Researcher at Queen Mary University of London
Publications - 482
Citations - 5030
Ebroul Izquierdo is an academic researcher from Queen Mary University of London. The author has contributed to research in topics: Image retrieval & Scalable Video Coding. The author has an hindex of 31, co-authored 474 publications receiving 4618 citations. Previous affiliations of Ebroul Izquierdo include University of Essex & Motorola.
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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY Editor-in-Chief
Chang Wen Chen,Hamid Gharavi,Thomas Sikora,Ishfaq Ahmad,John F. Arnold,Oscar Au,Mauro Barni,Vincent Bottreau,Jill Macdonald Boyce,Thomson Corp,Jianfei Cai,Homer H. Chen,Shao-Yi Chien,Mary Comer,Paulo Lobato Correia,Ricardo De Queiroz,Pascal Frossard,Toshiaki Fujii,Wen Gao,Richard Green,Yo-Sung Ho,Ebroul Izquierdo,Queen Mary,Rosa C. Lancini,Shipeng Li,Xin Li,Xuelong Li,Antonio Navarro,Sharath Pankanti,Justin Ridge,Yong Rui,Dan Schonfeld,Eckehard Steinbach,Sanghoon Sull,Huifang Sun,Clark N. Taylor,Deepak Turaga,Gene Wen,Thomas Wiegand,Dapeng Oliver Wu,Jar-Ferr Yang,Haoping Yu +41 more
TL;DR: This special issue, which focuses on event analysis in broad problem domains, has witnessed the effectiveness of using both static and temporal information in event recognition from other video sources.
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A Probabilistic Approach for Vision-Based Fire Detection in Videos
TL;DR: This paper proposes and analyze a new method for identifying fire in videos that analyzes the frame-to-frame changes of specific low-level features describing potential fire regions and combines them according to the Bayes classifier for robust fire recognition.
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Image classification with the use of radial basis function neural networks and the minimization of the localized generalization error
TL;DR: Through intensive experimentation, the resulting classifier outperforms other classifiers such as a multi-class support vector machines (SVMs) as well as ''standard'' RBFNNs (viz. those developed without the guidance offered by the optimization of the localized generalization error).
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Video streaming over P2P networks: Challenges and opportunities
TL;DR: Efficient (delay tolerant and intolerant) data sharing mechanisms in P2P and current video coding trends are elaborated in detail and the conclusion is drawn with key challenges and open issues related to video streaming over P1P.
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H.264/AVC to HEVC Video Transcoder Based on Dynamic Thresholding and Content Modeling
TL;DR: A novel transcoding architecture, in which the first frames of the sequence are used to compute the parameters so that the transcoder can learn the mapping for that particular sequence, is proposed and evaluates several transcoding algorithms from the H.264/AVC to the HEVC format.