Currently available Personal Video Recorders find and store whole TV programs. Our system, Video Scouting, not only finds and stores programs;it automatically segments and indexes story segments from the programs acco...
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ISBN:
(纸本)0780370414
Currently available Personal Video Recorders find and store whole TV programs. Our system, Video Scouting, not only finds and stores programs;it automatically segments and indexes story segments from the programs according to viewers' profiles. The extracted descriptions serve the viewers' content information requests for program segment selection, e.g. play the three minute interview with Hillary Clinton. To achieve this, the system combines information from the audio, visual, and transcript domains in a probabilistic framework based on Bayesian networks. In this paper we describe the overall architecture, a system implementation, and discuss some experimental results.
Collective motions, one of the coordinated behaviors in crowd system, widely exist in nature. Orderliness characterizes how well an individual will move smoothly and consistently with his neighbors in collective motio...
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ISBN:
(纸本)9781479902880
Collective motions, one of the coordinated behaviors in crowd system, widely exist in nature. Orderliness characterizes how well an individual will move smoothly and consistently with his neighbors in collective motions. It is still an open problem in computer vision. In this paper, we propose an orderliness descriptor based on correlation of interactive social force between individuals. In order to include the force correlation between two individuals in a distance, we propose a Social Force Correlation Propagation algorithm to calculate orderliness of every individual effectively and efficiently. We validate the effectiveness of the proposed orderliness descriptor on synthetic simulation. Experimental results on challenging videos of real scene crowds demonstrate that orderliness descriptor can perceive motion with low smoothness and locate disorder.
Pre-processing algorithms improve the quality of a compression system by removing unimportant data before encoding. This enhances both the visual quality and coding efficiency of the system. In this paper, we cast the...
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ISBN:
(纸本)0780367251
Pre-processing algorithms improve the quality of a compression system by removing unimportant data before encoding. This enhances both the visual quality and coding efficiency of the system. In this paper, we cast the pre-processing problem in the operational rate-distortion framework. Filtering the displaced frame difference is the focus, and the proposed method couples the choice of the quantization scale to the response of the prefilter. Coding errors are then addressed by penalizing significant differences between coded blocks. Finally, experimental results illustrate the efficacy of the method within the context of an MPEG-2 coding scenario.
image quality assessment is always a hot research topic in the field of imageprocessing. Structural Similarity image Measurement (SSIM) is an image quality assessment algorithm with the advantages of simplicity, high...
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ISBN:
(纸本)9781479989201
image quality assessment is always a hot research topic in the field of imageprocessing. Structural Similarity image Measurement (SSIM) is an image quality assessment algorithm with the advantages of simplicity, high efficiency and better consistence. Its evaluation of performance is better than PNSR and MSE. However, it often fails when assessing badly distorted or cross distorted images. In this paper, we proposed a new method on the improved method of SSIM and the method of based on visual region of interest combination. This improved method of SSIM takes the histogram concentration as the main structural information of an image. It used histogram concentration to calculate the fuzzy degree of the image. Finally, we can obtain the structure similarity value of the image. The experiment results show that, compared with the SSIM model, the proposed RoiHSSIM model is more close to the human visual system and can access the quality of fault images more precisely.
This paper presents a noise-aided dynamic range compression algorithm using a stochastic resonance model in spatial domain. An input statistics-dependent stochastic resonance (ISSR) model, that is designed for contras...
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ISBN:
(纸本)9781467373142
This paper presents a noise-aided dynamic range compression algorithm using a stochastic resonance model in spatial domain. An input statistics-dependent stochastic resonance (ISSR) model, that is designed for contrast enhancement of dark images, is used here to enhance an image with both bright and dark areas. The underilluminated regions of such an image are selected as the De Vries Rose region from a human visual system-based segmentation algorithm, and then processed using the ISSR model. It is observed that by semi-adaptively changing the processing parameters with iteration, the processed dark regions and the unprocessed bright regions of an image smoothly merge producing a quality of dynamic range compression in the image. The performance of the proposed algorithm is characterized using image quality index for tone-mapped images and a no-reference perceptual quality measure. Results and comparative analysis suggest notable performance of the proposed algorithm with fewer iteration.
A robust parametric motion estimation algorithm is presented in this paper. The algorithm is an extension of the 4-2-1 pixel hierarchical search used in previous MPEG-7 visual eXperimental Model (XM) algorithm of the ...
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ISBN:
(纸本)0780367251
A robust parametric motion estimation algorithm is presented in this paper. The algorithm is an extension of the 4-2-1 pixel hierarchical search used in previous MPEG-7 visual eXperimental Model (XM) algorithm of the MPEG-7 standard. A refined version of the Levenberg-Marquardt algorithm is used in a hierarchical coarser-to-fine scale-space that makes sure that optimization is done in steps that always decrease the displacement and avoids local minimizers, The application of the algorithm in image mosaic construction is shown, demonstrating the ability of the algorithm to handle frames with large transitions. The algorithm was accepted for inclusion in the latest MPEG-7 visual XM and Multimedia Description Schemes XM.
Single image deraining is an important problem in many computer vision tasks because rain streaks can severely degrade the image quality. Recently, deep convolution neural network (CNN) based single image deraining me...
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ISBN:
(纸本)9781665475921
Single image deraining is an important problem in many computer vision tasks because rain streaks can severely degrade the image quality. Recently, deep convolution neural network (CNN) based single image deraining methods have been developed with encouraging performance. However, most of these algorithms are designed by stacking convolutional layers, which encounter obstacles in learning abstract feature representation effectively and can only obtain limited features in the local region. In this paper, we propose a recurrent multi-connection fusion network (RMCFN) to remove rain streaks from single images. Specifically, the RMCFN employs two key components and multiple connections to fully utilize and transfer features. Firstly, we use a multi-scale fusion memory block (MFMB) to exploit multi-scale features and obtain long-range dependencies, which is beneficial to feed useful information to a later stage. Moreover, to efficiently capture the informative features on the transmission, we fuse the features of different levels and employ a multi-connection manner to use the information within and between stages. Finally, we develop a dual attention enhancement block (DAEB) to explore the valuable channel and spatial components and only pass further useful features. Extensive experiments verify the superiority of our method in visual effect and quantitative results compared to the state-of-the-arts.
This paper introduces a new class of bases, called bandelet bases, which decompose the image along multiscale vectors that are elongated in the direction of a geometric flow. This geometric flow indicates the directio...
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ISBN:
(纸本)0819450235
This paper introduces a new class of bases, called bandelet bases, which decompose the image along multiscale vectors that are elongated in the direction of a geometric flow. This geometric flow indicates the direction in which the image grey levels have regular variations. The image decomposition in a bandelet basis is implemented with a fast subband filtering algorithm. Bandelet bases lead to optimal approximation rates for geometrically regular images. For image compression, the bandelet basis geometry is optimized with a fast best basis algorithm. Comparisons are made for image compression with wavelet bases.
Meaningful region is the intermediate level between the original image and the interesting object of image. This level is an effective visual level for the representation of images and the successful extraction of mea...
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ISBN:
(纸本)0819439886
Meaningful region is the intermediate level between the original image and the interesting object of image. This level is an effective visual level for the representation of images and the successful extraction of meaningful regions from images helps to perform semantic segmentation. This paper proposes a scheme for roughly extracting meaningful regions in an image. By using multi-dimensional low-level feature analysis the local level of reliability of different features can be determined in order to adaptively weight the contribution of each feature to the segmentation process. Since the large variance of one feature always indicates that this feature would distinguish different objects clearly, a new weighted non-parametric clustering algorithm in the density space is implemented with suitably decided weights for different features. This permits us to utilize all. the features efficiently and to extract semantic meaning from images. The above technique is proposed along with a retrieval application of landscape images. In this application, the object recognition plays an important role. The meaningful regions extracted should be merged into objects and more subtly semantic meaning could be obtained. Experiments on extracting meaningful regions both from still images and video clips are carried out with some satisfactory results.
There are several ways to display color data of a color image. In this paper we present different methods that we have developed in order to understand and to analyze color image information. These methods use traditi...
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ISBN:
(纸本)0819450235
There are several ways to display color data of a color image. In this paper we present different methods that we have developed in order to understand and to analyze color image information. These methods use traditional 2D and 3D visualization model associated with specific color transformation. We also introduce a new multidimensional visualization model usefull to analyse spatiocolorimetric data.
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