Probabilistic Multimodality Fusion for Event based Home Photo Clustering
Tao Mei
Bin Wang
Xian-Sheng Hua
He-Qin Zhou
Shipeng Li
MOE-MS Key Lab. of Multimedia Comput. & Commun., Univ. of Sci. & Technol. of China, Hefei;
This paper appears in: Multimedia and Expo, 2006 IEEE International Conference on
Publication Date: 9-12 July 2006
On page(s): 1757-1760
Location: Toronto, Ont.,
ISBN: 1-4244-0366-7
INSPEC Accession Number: 9112745
Digital Object Identifier: 10.1109/ICME.2006.262891
Current Version Published: 2006-12-26
Abstract
This paper presents a novel probabilistic approach to fusing multimodal metadata for event based home photo clustering. Photo events are characterized by the coherence of multimodality including time, content and camera settings. We incorporate these multimodal metadata into a unified probabilistic framework, in which event is taken as a latent semantic concept and discovered by fitting a generative model through an expectation-maximization (EM) algorithm. This approach is general and unsupervised, without any training procedure or predefined threshold. The experimental evaluations on 14 k photos taken by 10 amateur photographers have indicated the effectiveness and efficiency of the proposed framework in browsing and searching personal photo collections
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