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Alberto Del Bimbo
Researcher at University of Florence
Publications - 500
Citations - 10851
Alberto Del Bimbo is an academic researcher from University of Florence. The author has contributed to research in topics: Computer science & Image retrieval. The author has an hindex of 45, co-authored 460 publications receiving 9243 citations. Previous affiliations of Alberto Del Bimbo include University of Modena and Reggio Emilia & University of Brescia.
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Visual Information Retrieval
TL;DR: 1. Visual Information Retrieval 2. Image Retrival by Color Similarity 3. Image retrieval by Texture Similarity 4. image Retrieva by Shape Similarity 5. imageRetrievalBy Spatial Relationships 6. Content-Based Video Retrivel
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3-D Human Action Recognition by Shape Analysis of Motion Trajectories on Riemannian Manifold
TL;DR: This paper proposes a new framework to extract a compact representation of a human action captured through a depth sensor, and enable accurate action recognition, and results with state-of-the-art methods are reported.
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Person Re-Identification by Iterative Re-Weighted Sparse Ranking
TL;DR: The approach makes use of soft- and hard- re-weighting to redistribute energy among the most relevant contributing elements and to ensure that the best candidates are ranked at each iteration of an iterative extension to sparse discriminative classifiers capable of ranking many candidate targets.
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Semantic annotation of soccer videos: automatic highlights identification
TL;DR: This paper presents a system that performs automatic annotation of the principal highlights in soccer video, suited for both production and posterity logging.
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Copy-move forgery detection and localization by means of robust clustering with J-Linkage
Irene Amerini,Lamberto Ballan,Roberto Caldelli,Alberto Del Bimbo,Luca Del Tongo,Giuseppe Serra,Giuseppe Serra +6 more
TL;DR: A novel approach is presented for copy-move forgery detection and localization based on the JLinkage algorithm, which performs a robust clustering in the space of the geometric transformation, which outperforms other similar state-of-the-art techniques.