The neural mechanism of memory has a very close relation with the problem of representation in Artificial Intelligence (AI). In this paper a computational model is proposed to simulate the network of neurons in brain ...
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Production system programs are being routinely used in diverse tasks. With the increasing acceptance, demands on production system implementations is growing. Currently several research efforts are trying to use produ...
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The paper presents a novel fast matching algorithm between airborne and satellite-borne SAR images so as to efficiently integrate SAR images into GPSISINS navigation system. Because the character such as gray level an...
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A number of different approaches have been presented in the recent past addressing the issue of image retrieval using color and texture features. Most of these methods are based on elaborate mathematical modeling, inc...
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The Karhunen-Loeve transform (KLT) is applied to the analysis of dynamic sequences of thermograms describing the temporal evolution of body surface temperature following the application of an external thermal stimulus...
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ISBN:
(纸本)0818608625
The Karhunen-Loeve transform (KLT) is applied to the analysis of dynamic sequences of thermograms describing the temporal evolution of body surface temperature following the application of an external thermal stimulus. The KLT may be evaluated either along the spatial or temporal dimensions of the data;the duality of both representations is emphasized. An example is presented to illustrate that the KLT allows an efficient data reduction and facilitates tumor detection by highlighting physiologically important abnormalities in the time behavior of thermal patterns.
In the field of human pose estimation, HRNet (high-resolution network) has excellent performance. In order to make it deployable in mobile devices with weak computing power, we designed it to be lightweight. Through s...
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Face recognition is one of the most effective image-processing.applications and is essential in the technological era. The identification of the facial image is a current problem for authentication purposes, particula...
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In this paper we propose a real-time algorithm for detecting and tracking moving objects in a video sequence. Based on the on-line boosting framework, our algorithm is able to detect an object as a member of a class, ...
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In this paper, we address a few important image analysis problems, which are fundamental to the design of Perceptual User Interface (PUI). We use an inexpensive stationary desktop camera to collect the video streams a...
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ISBN:
(纸本)0819437034
In this paper, we address a few important image analysis problems, which are fundamental to the design of Perceptual User Interface (PUI). We use an inexpensive stationary desktop camera to collect the video streams and use them as input to the system. We present an algorithm for segmenting moving: foreground object of interest from a complex, but stationary background. This algorithm can cope with illumination changes due to shadows, Automatic Exposure Correction (AEC) and long term illumination changes in the environment. The segmentation is done real time and works well for both indoor and outdoor scenes. The detected foreground is recognized as human being based on head shoulder profile. The head shoulder profile is extracted as a pattern using an unique physics based approach, which is robust to noise and eliminates the need of median filtering to remove noise. We obtain Ring Data Vectors as features from the pattern, which is used to classify them into different clusters. The patterns which are similar form a cluster in the N dimensional vector space formed by the orthogonal basis of Ring Data Vectors. a data set for each possible cluster is formed by initial training and manual classification of different sets of patterns belonging to different human pose. Unknown new pattern extracted from the segmented foreground is synthetically recognized and classified into one of the existing template pattern. The system has been used in design of Visual computer games and can be used in the design of PUI's for pervasive computing applications, surveillance etc.
In this work, we propose a novel approach to video segmentation that operates in bilateral space. We design a new energy on the vertices of a regularly sampled spatiotemporal bilateral grid, which can be solved effici...
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ISBN:
(纸本)9781467388511
In this work, we propose a novel approach to video segmentation that operates in bilateral space. We design a new energy on the vertices of a regularly sampled spatiotemporal bilateral grid, which can be solved efficiently using a standard graph cut label assignment. Using a bilateral formulation, the energy that we minimize implicitly approximates long-range, spatio-temporal connections between pixels while still containing only a small number of variables and only local graph edges. We compare to a number of recent methods, and show that our approach achieves state-of-the-art results on multiple benchmarks in a fraction of the runtime. Furthermore, our method scales linearly with image size, allowing for interactive feedback on real-world high resolution video.
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