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Young children need their parents' love and care but their parents are not always available to tell them stories. This motivates our proposal of a Smart Teddy Bear, a vision-based story teller, to assist young children in their social-emotional growth. When a young child wants to listen to a story, he or she simply opens any page in that book before a Smart Teddy Bear and the system automatically...
Histograms are used in almost every aspect of image processing and computer vision, from visual descriptors to image representations. Histogram intersection kernel (HIK) and support vector machine (SVM) classifiers are shown to be very effective in dealing with histograms. This paper presents contributions concerning HIK SVM for image classification. First, we propose intersection coordinate descent...
Considering the simplicity and fast training speed of Haar-like features, the high detecting precision of HOG features, a combined method is proposed on the basis of the two features. Several rectangular features which can describe local human characteristics based on original features are added. The combined method can retain the precision of HOG features and increase the speed of detection at the...
We propose a novel approach for content based color image classification using Support Vector Machine (SVM). Traditional classification approaches deal poorly on content based image classification tasks being one of the reasons of high dimensionality of the feature space. In this paper, color image classification is done on features extracted from histograms of color components. The benefit of using...
The combination of local features, complementary feature types, and relative position information has been successfully applied to many object-class recognition tasks. Stacking is a common classification approach that combines the results from multiple classifiers, having the added benefit of allowing each classifier to handle a different feature space. However, the standard stacking method by its...
Object detection and classification have received increased attention recently from computer vision and image processing researchers. Image processing views this problem at a much lower level as compared to machine learning and linear algebraic analysis which focus on the overall statistics of object classes given sufficient data. A good algorithm uses both these approaches to its advantage. It is...
In this paper, a new, simple but effective method is proposed for blind image steganalysis, which is based on run-length histogram analysis. Higher-order statistics of characteristic functions of three types of image run-length histograms are selected as features. Support vector machine is used as classifier. Experimental results demonstrate that the proposed scheme significantly outperforms prior...
This paper proposes a novel face representation approach, local Gabor binary mapping pattern (LGBMP), for multi-view gender classification. In this approach, a face image is first represented as a series of Gabor magnitude pictures (GMP) by applying multi-scale and multi-orientation Gabor filters. Each GMP is then encoded as a LGBP image where a uniform local binary pattern (LBP) operator is used...
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