In this paper, we present a general framework for solving the shape from shading problem for a class of surfaces called implicit surfaces by applying image synthesis techniques from computergraphics. The method relie...
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In this paper, we present a general framework for solving the shape from shading problem for a class of surfaces called implicit surfaces by applying image synthesis techniques from computergraphics. The method relies on iterative synthesis of images from object descriptions in order to minimize an error function. The technique is illustrated in detail for quadric surfaces, with the ellipsoid as the specific example. The advantage of this approach is that reconstructing the shape of objects from shading is possible even under very general imaging conditions.
We present an Audio-visual person authentication system which extracts several novel ldquovisualized-speech-featuresrdquo (VSF) from the spoken-password and multiple face profiles using a simple user-interface and com...
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We present an Audio-visual person authentication system which extracts several novel ldquovisualized-speech-featuresrdquo (VSF) from the spoken-password and multiple face profiles using a simple user-interface and combine these features to deliver high performance and resilience against imposter attacks. The spoken password is converted to a string of images formed by several visualized speech features. A compressed form of these VSFs preserves speaker identity in a compact manner. Simulation results on an in-house 210-user AV-user-ID database collected with wide variations of users in real-life office environments demonstrate separable distributions of client and imposter scores (0% EER), while offering low storage and computational complexities compared to conventional AV user-recognition methods.
Light field cameras have a unique feature of capturing the direction of light rays along with its intensity. This additional information is used to estimate the depth of a 3-D scene. Recently a considerable amount of ...
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The Mixed Raster Content (MRC) ITU document compression standard (T.44) specifies a multi-layer representation of a compound document. It is expected that higher compression can be achieved if more efficient compressi...
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The Mixed Raster Content (MRC) ITU document compression standard (T.44) specifies a multi-layer representation of a compound document. It is expected that higher compression can be achieved if more efficient compression standards are used to compress each layer. In this paper we present an MRC compound document codec that uses H.264/AVC operating in INTRA mode to encode Background/Foreground layers and JBIG2 to encode the binary Mask layer. We also present a threshold-based layer segmentation algorithm and an iterative data-filling algorithm for redundant regions. The result is an unrivaled performance for compressing compound documents as demonstrated by our experiments.
We present a simple approach for facial expression recognition from images using the principle of sparse representation using a learned dictionary. Visual appearance based feature descriptors like histogram of oriente...
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Advances in digital content transmission have increased in the past few years. Security and privacy issues of the transmitted data have become an important concern in multimedia technology. In this paper, we propose a...
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Advances in digital content transmission have increased in the past few years. Security and privacy issues of the transmitted data have become an important concern in multimedia technology. In this paper, we propose a computationally efficient and secure video encryption algorithm. This makes secure video encryption feasible for real-time applications without any extra dedicated hardware. We achieve computational efficiency by exploiting the frequently occurring patterns in the DCT coefficients of the video data. Computational complexity of the encryption is made proportional to the influence of the DCT coefficients on the visual content. On an average, our algorithm takes only 8.32 ms of encryption time per frame.
Converting a grayscale image to a visually plausible and perceptually meaningful color image is an exciting research topic in computervision and graphics. However, predicting the chrominance channels from a grayscale...
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This paper presents a new color document image binarization that is suitable for palm leaf manuscripts and color document images. The proposed method consists of two steps: a pre-processing procedure using low-pass Wi...
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This paper presents a new color document image binarization that is suitable for palm leaf manuscripts and color document images. The proposed method consists of two steps: a pre-processing procedure using low-pass Wiener filter, and contrast adaptive binarization for segmentation of text from the background. Firstly, in the pre-processing stage, low-pass Wiener filter is used to eliminate noisy areas, smoothing of background texture as well as contrast enhancement between background and text areas. Finally, binarization is performed by using contrast adaptive binarization method in order to extract useful text information from low quality document *** techniques are tested on a set of palm leaf manuscript images/color document images. The performance of the algorithm is demonstrated on by palm leaf manuscripts/color documents distorted with show-through effects, uneven background color and localized spot.
In this paper, we propose a hybrid Tabu Expectation Maximization (TEM) Algorithm for segmentation of Brain Magnetic Resonance (MR) images in both supervised and unsupervised framewrok. Gaussian Hidden Markov Random Fi...
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This book – in conjunction with the volumes LNCS 8588 and LNAI 8589 – constitutes the refereed proceedings of the 10th International conference on Intelligent Computing, ICIC 2014, held in Taiyuan, China, in August ...
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ISBN:
(数字)9783319093307
ISBN:
(纸本)9783319093291
This book – in conjunction with the volumes LNCS 8588 and LNAI 8589 – constitutes the refereed proceedings of the 10th International conference on Intelligent Computing, ICIC 2014, held in Taiyuan, China, in August 2014. The 58 papers of this volume were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections such as machine learning; neural networks; imageprocessing; computational systems biology and medical informatics; biomedical informatics theory and methods; advances on bio-inspired computing; protein and gene bioinformatics: analysis, algorithms, applications.
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