In this paper, an end-to-end real-time adaptive protocol for multimedia transmission is presented. The transmission rate is determined by the quadratic probing algorithm that can obtain the maximal utilization of the ...
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In this paper, a powerful open Multiple Instance Learning (MIL) framework is proposed. Such an open framework is powerful since different sub-methods can be plugged into the framework to generate different specific Mu...
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Recent research effort in Content-Based Image Retrieval (CBIR) focuses on bridging the gap between low-level features and high-level semantic contents of images as this gap has become the bottleneck of CBIR. In this p...
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ISBN:
(纸本)1581137265
Recent research effort in Content-Based Image Retrieval (CBIR) focuses on bridging the gap between low-level features and high-level semantic contents of images as this gap has become the bottleneck of CBIR. In this paper, an effective image database retrieval framework using a new mechanism called the Markov Model Mediator (MMM) is presented to meet this demand by taking into consideration not only the low-level image features, but also the high-level concepts learned from the history of user's access pattern and access frequencies on the images in the database. Also, the proposed framework is efficient in two aspects: 1) Overhead for real-time training is avoided in the image retrieval process because the high-level concepts of images are captured in the off-line training process. 2) Before the exact similarity matching process, Principal Component Analysis (PCA) is applied to reduce the image search space. A training subsystem for this framework is implemented and integrated into our system. The experimental results demonstrate that the MMM mechanism can effectively assist in retrieving more accurate results from image databases. Copyright 2003 ACM.
This paper presents a content-based image retrieval (CBIR) system that incorporates real-valued multiple instance learning (MIL) into the user relevance feedback (RF) to learn the user's subjective visual concepts...
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Traffic video analysis can provide a wide range of useful information such as vehicle identification, traffic flow, to traffic planners. In this paper, a framework is proposed to analyze the traffic video sequence usi...
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We present a mechanism called the Markov model mediator (MMM) to facilitate the effective retrieval for content-based image retrieval (CBIR). Different from the common methods in content-based image retrieval, our sto...
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An embodied virtual face-to-face communication system is developed for three human interaction supports and the analysis by synthesis. The system provides networked virtual communication environment in which three rem...
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An embodied virtual face-to-face communication system is developed for three human interaction supports and the analysis by synthesis. The system provides networked virtual communication environment in which three remote talkers can share embodied interactions by observing their interaction of avatars called VirtualActors including themselves in the same virtual space. The effectiveness of the system is demonstrated by the sensory evaluation of the communication experiment and selected most favorite viewpoint when talker's own VA was semitransparently presented in 8 groups, 3 talkers per group. The importance of mutual embodied sharing in communication is also clarified. The system would be expected to form the foundation of group embodied interaction support system as well as the analysis and understanding of group embodied interaction.
Understanding and learning the subjective aspect of humans in Content-Based Image Retrieval has been an active research field during the past few years. However, how to effectively discover users’ concept patterns wh...
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It is very important to provide analysts with guaranteed error bounds for approximate aggregate queries in many current enterprise applications such as the decision support systems. In this paper, we propose a general...
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The interaction of solid particles with various surfaces has been experiencing growing interest in the area of nanotechnology, colloidal science and biology. In this paper interactions of solid particles with various ...
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The interaction of solid particles with various surfaces has been experiencing growing interest in the area of nanotechnology, colloidal science and biology. In this paper interactions of solid particles with various surfaces using piezoelectric thickness shear mode (TSM) sensors have been studied. A mechanical model has been presented to evaluate the effect of particle loading on the behavior of a TSM sensor. The main sources contributing to the interaction, such as Van der Waals force, gravitational force and electrostatic force, are discussed. Experimental results have shown that the resonant frequency of a TSM sensor depends on the coupling conditions of micro- or nano- particles loaded on the surfaces of a TSM sensor, which is predicted by the theoretical model. The results show that this TSM sensor technique can provide the information of the coupling, such as the binding energy between the particles and the sensor surfaces, and may promote the applications of TSM sensors in characterizing the properties of the loaded particles.
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