7 Result(s)
within
English
Computer Graphics
Liang-Tien Chia
Conference Paper
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Chapter and Conference Paper
Salient Region Detection Using Weighted Feature Maps Based on the Human Visual Attention Model
Detection of salient regions in images is useful for object based image retrieval and browsing applications. This task can be done using methods based on the human visual attention model [1], where feature map...
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Chapter and Conference Paper
Multimedia Web Services for an Object Tracking and Highlighting Application
Over the years, multimedia applications are getting increasingly more complex and large in scale. Multimedia Web Service is identified as one of the possible solutions to meet the challenges. The advantages of...
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Chapter and Conference Paper
Motion Context: A New Representation for Human Action Recognition
One of the key challenges in human action recognition from video sequences is how to model an action sufficiently. Therefore, in this paper we propose a novel motion-based representation called Motion Context (MC...
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Chapter and Conference Paper
Image-to-Class Distance Metric Learning for Image Classification
Image-To-Class (I2C) distance is first used in Naive-Bayes Nearest-Neighbor (NBNN) classifier for image classification and has successfully handled datasets with large intra-class variances. However, the perfo...
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Chapter and Conference Paper
Kernel Sparse Representation for Image Classification and Face Recognition
Recent research has shown the effectiveness of using sparse coding(Sc) to solve many computer vision problems. Motivated by the fact that kernel trick can capture the nonlinear similarity of features, which ma...
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Chapter and Conference Paper
Salient Region Detection by Jointly Modeling Distinctness and Redundancy of Image Content
Salient region detection in images is a challenging task, despite its usefulness in many applications. By modeling an image as a collection of clusters, we design a unified clustering framework for salient reg...
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Chapter and Conference Paper
Learning Class-to-Image Distance via Large Margin and L1-Norm Regularization
Image-to-Class (I2C) distance has demonstrated its effectiveness for object recognition in several single-label datasets. However, for the multi-label problem, where an image may contain several regions belong...
