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ABSTRACT: The classification of semantic human images is an active problem in interpreting multimedia images. Many researchers have attempted to improve the semantic model by using semantic action concepts. Although previous techniques, such as keyword definition and using content features of human action, have been applied, most results indicate that human images cannot be mapped into actual image meaning. The aim of this paper is to classify semantic human images by integrating relevant image contents and the energy expenditure. We proposed a new semantic model called the energy-action (EA) model, which analyzes the energy intensity of body parts with essential reference points. The EA model is presented in two stages: human action analysis and energy intensity analysis. Our results indicate that the proposed approach offers significant performance improvements in the interpretation of semantic human images.
Communications and Information Technologies, 2007. ISCIT '07. International Symposium on; 11/2007
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ABSTRACT: Semantic personal image classification is an attention problem in multimedia image retrieval. In our previous work [Chinpanchana, S et al., 2004], we classified semantic images into business, leisure, and sport categories by integrating the frequency pattern relationships between body parts and objects. However, the accuracy mainly depends on their objects. In the images that have high semantic complexities, the body movement play important solve on the meaning of image. In this paper, we present a new model to achieve more effective classifier called an energy expenditure model (EE). The EE model is based on the concept that human subjects in different classes of images are likely to spend different amounts of energy. The angular position and flexion forces are related into each body part. Experimental results show that the EE a can achieve an improvement of semantic images.
Communications and Information Technology, 2005. ISCIT 2005. IEEE International Symposium on; 11/2005
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ABSTRACT: Our current understanding of how emotions are expressed in speech is still very limited. Part of the difficulty has been the lack of understanding of the underlying mechanisms. Here we report the findings of a somewhat unconventional investigation of emotional speech. Instead of looking for direct acoustic correlates of multiple emotions, we tested a specific theory, the size code hypothesis of emotional speech, about two emotions – anger and happiness. According to the hypothesis, anger and happiness are conveyed in speech by exaggerating or understating the body size of the speaker. In two studies consisting of six experiments, we synthesized vowels with a three-dimensional articulatory synthesizer with parameter manipulations derived from the size code hypothesis, and asked Thai listeners to judge the body size and emotion of the speaker. Vowels synthesized with a longer vocal tract and lower F0 were mostly heard as from a larger person if the length and F0 differences were stationary, but from an angry person if the vocal tract was dynamically lengthened and F0 was dynamically lowered. The opposite was true for the perception of small body size and happiness. These results provide preliminary support for the size code hypothesis. They also point to potential benefits of theory-driven investigations in emotion research.
Phonetica 08/1970; 65(4):210-230. · 1.60 Impact Factor
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International journal of signal processing. 3:129-134.
