Over the last decade perceptually based image compression has gained significant importance. This is because it relies on Human Visual Perception (HVP) in measuring the reconstruction quality in the compression proces...
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Over the last decade perceptually based image compression has gained significant importance. This is because it relies on Human Visual Perception (HVP) in measuring the reconstruction quality in the compression process, as humans are the end users for images. Visual data that is perceived by humans can be characterized in terms of three parameters. Magnitude, Phase and Orientation of the spatial frequency content. While existing perceptually based image compression techniques exploits the first parameter, the novel contribution of this paper is its focus on the use of phase data for perceptually based texture compression. In this paper a HVS based texture characterization approach is applied to measure the perceived (by humans) phase coherence in the image. Then images are more compressed after removing the unperceived phase redundancy. Finally subjective tests are performed to measure the reconstruction quality of the proposed compression approach. The proposed compression algorithm has been applied in the JPEG2000 framework. Simulation results that demonstrate the efficiency of the proposed approach are presented.
Complex human motion (e.g. dance) sequences are typically analyzed by segmenting them into shorter motion sequences, called gestures. However, this segmentation process is subjective, and varies considerably from one ...
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Complex human motion (e.g. dance) sequences are typically analyzed by segmenting them into shorter motion sequences, called gestures. However, this segmentation process is subjective, and varies considerably from one choreographer to another. Dance sequences also exhibit a large vocabulary of gestures. In this paper, we propose an algorithm called hierarchical activity segmentation. This algorithm employs a dynamic hierarchical layered structure to represent human anatomy, and uses low-level motion parameters to characterize motion in the various layers of this hierarchy, which correspond to different segments of the human body. This characterization is used with a naive Bayesian classifier to derive choreographer profiles from empirical data that are used to predict how particular choreographers segment gestures in other motion sequences. When the predictions were tested with a library of 45 3D motion capture sequences (with 185 distinct gestures) created by 5 different choreographers, they were found to be 93.3% accurate.
A human centered pragmatic approach to the design and implementation of a vibrotactile belt is presented in this paper. Based on (a) extensive usability feedback we've collected over the past year, and (b) a thoro...
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A human centered pragmatic approach to the design and implementation of a vibrotactile belt is presented in this paper. Based on (a) extensive usability feedback we've collected over the past year, and (b) a thorough survey of existing design guidelines from the literature, we propose a set of design guidelines for the development of haptic belts that can span seamlessly across various applications. These guidelines cover three important aspects for haptic belts: functionality, performance and usability, which are vital for longitudinal use by end users. Taking a human-centric approach from these design guidelines, we demonstrate the construction of a wirelessly controlled haptic belt design that is versatile, usable and practical. Implementation details of the belt are given, along with a preliminary usability study and a brief review of some of the important application areas of haptic belts. Results from the usability study reveal that participants were very pleased with the proposed haptic belt, and found it to be easy to wear and use.
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