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Manifold-ranking based image retrieval
TLDR
MRBIR first makes use of a manifold ranking algorithm to explore the relationship among all the data points in the feature space, and then measures relevance between the query and all the images in the database accordingly, which is different from traditional similarity metrics based on pair-wise distance.
A user attention model for video summarization
TLDR
A generic framework of video summarization based on the modeling of viewer's attention is presented, which takes advantage of computational attention models and eliminates the needs of complex heuristic rules inVideo summarization.
Blur detection for digital images using wavelet transform
TLDR
A new blur detection scheme is proposed in this paper, which can determine whether an image is blurred or not and to what extent animage is blurred.
An efficient and effective region-based image retrieval framework
TLDR
An image retrieval framework that integrates efficient region-based representation in terms of storage and complexity and effective on-line learning capability and a region weighting strategy is introduced to optimally weight the regions and enable the system to self-improve.
A probabilistic model for retrospective news event detection
TLDR
This work proposes a probabilistic model to incorporate both content and time information in a unified framework for retrospective news event detection and builds an interactive RED system, HISCOVERY, which provides additional functions to present events, Photo Story and Chronicle.
Online video recommendation based on multimodal fusion and relevance feedback
TLDR
This paper presents a novel online video recommendation system based on multimodal fusion and relevance feedback, and is able to recommend videos without users' profiles.
Automated annotation of human faces in family albums
TLDR
The experimental evaluation has been conducted within a family album of few thousands of photographs and the results show that the proposed approach is effective and efficient in automated face annotation in family albums.
Learning a semantic space from user's relevance feedback for image retrieval
TLDR
This work experiments with using spectral methods to infer a semantic space from user's relevance feedback, so that the system will gradually improve its retrieval performance through accumulated user interactions.
Learning in Region-Based Image Retrieval
TLDR
In this paper, several effective learning algorithms using global image representations are adjusted and introduced to regionbased image retrieval (RBIR) inspired by feature re-weighting ones.
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