By Guoping Qiu, Kin Man Lam, Hitoshi Kiya, Xiang-Yang Xue, C.-C. Jay Kuo, Michael S. Lew
This ebook constitutes the lawsuits of the eleventh Pacific Rim convention on Advances in Multimedia details Processing, held in Shanghai in September 2010.
Read Online or Download Advances in Multimedia Information Processing -- PCM 2010, Part II: 11th Pacific Rim Conference on Multimedia, Shanghai, China, September 21-24, 2010 Proceedings PDF
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Additional resources for Advances in Multimedia Information Processing -- PCM 2010, Part II: 11th Pacific Rim Conference on Multimedia, Shanghai, China, September 21-24, 2010 Proceedings
Table 1. shows some of the labels and images: We randomly selected half of the images as training data and others as testing data. Original feature vector and reduced feature vector by diﬀerent dimensionality reduction methods are respectively used to train the classiﬁers for classiﬁcation over the testing data. Finally we evaluate the performance of the classiﬁers by classiﬁcation accuracy achieved. 3 Comparison of Diﬀerent Dimensionality Reduction Methods In our experiments, we compare diﬀerent dimensionality reduction methods including PCA, kernel PCA, LPP, CUR matrix decomposition, and stacked autoencoder.
Therefore, the number of visual words to be used for the description of certain image semantic should be far less with structured sparsity. As a result, some sparsity-based multilabel annotation approaches have been studied to impose structural penalty on label space. Motivated that it is useful to reduce high-dimensional feature space to a lower-dimensional semantic space oriented by corresponding multiple labels, a multi-label sparse coding framework was proposed in which a multi-label linear embedding approach utilize multi-label information for dimension reduction of visual features (MLE).
These text information provides another possible dimension of media information and has potential to improve the recommendation quality associated with a user. Moreover, another fundamental but challenging research question is how to formulate users’ queries to express their real information needs effectively. Due to complexity of media content, good model effectiveness can not be expected using descriptor generation scheme based on single modality. In this context, the development of advanced fusion technique can be extremely useful to fully integrate the power of information from different sources.
Advances in Multimedia Information Processing -- PCM 2010, Part II: 11th Pacific Rim Conference on Multimedia, Shanghai, China, September 21-24, 2010 Proceedings by Guoping Qiu, Kin Man Lam, Hitoshi Kiya, Xiang-Yang Xue, C.-C. Jay Kuo, Michael S. Lew