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10th indian conference on computer vision, graphics and image processing (ICVGIP)

作者： Mopuri, Konda Reddy Babu, R. Venkatesh Indian Inst Sci Bangalore Karnataka India

ISBN: (纸本)9781450347532

Learning image representations has been an interesting and challenging problem. When users upload images to photo sharing websites, they often provide multiple textual tags for ease of reference. these tags can reveal significant information about the content of the image such as the objects present in the image or the action that is taking place. Approaches have been proposed to extract additional information from these tags in order to augment the visual cues and build a multi-modal image representation. However, the existing approaches do not pay much attention to the semantic meaning of the tags while they encode. In this work, we attempt to enrich the image representation with the tag encodings that leverage their semantics. Our approach utilizes neural network based natural language descriptors to represent the tag information. By complementing the visual features learned by convnets, our approach results in an efficient multi-modal image representation. Experimental evaluation suggests that our approach results in a better multi-modal image representation by exploiting the two data modalities for classification on benchmark datasets.

关键词： Multi-modal image representation neural embeddings natural language descriptors word2vec text encoding image description

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On the view synthesis of man-made scenes using uncalibrated cameras

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PATTERN RECOGNITION LETTERS 2007年第3期28卷 384-393页

作者： Sharma, Geetika Chaudhury, Santanu Srivastava, J. B. Indian Inst Technol Dept Elect Engn New Delhi 110016 India Indian Inst Technol Dept Math New Delhi 110016 India

We have attempted the problem of novel view synthesis of scenes containing man-made objects from images taken by arbitrary, uncalibrated cameras. Under the assumption of availability of the correspondence of three vanishing points, in general position, we propose two techniques. the first is a transfer-based scheme which synthesizes new views with only a translation of the virtual camera and computes z-buffer values for handling occlusions in synthesized views. the second is a reconstruction-based scheme which synthesizes arbitrary new views in which the camera can undergo rotation as well as translation. We present experimental results to establish the validity of both formulations. (c) 2006 Published by Elsevier B.V.

关键词： image-based rendering novel view synthesis uncalibrated cameras

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Adaptive Artistic Stylization of images 16

Adaptive Artistic Stylization of Images

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10th indian conference on computer vision, graphics and image processing (ICVGIP)

作者： Deshpande, Ameya Raman, Shanmuganathan IIT Gandhinagar Gandhinagar Gujarat India

ISBN: (纸本)9781450347532

In this work, we present a novel non-photorealistic rendering method which produces good quality stylization results for color images. the procedure is driven by saliency measure in the foreground and the background region. We start with generating saliency map and simple thresholding based segmentation to get rough estimation of the foreground background mask. We improve this mask by using a scribble based method where the scribbles for foreground-background regions are automatically generated from the previous rough estimation. Followed by the mask generation, we proceed with an iterative abstraction process which involves edge preserving blurring and edge detection. the number of iterations of the abstraction process to be performed in the foreground and background regions are decided by tracking the changes in saliency measure in the foreground and the background regions. Performing unequal number of iterations helps to improve the average saliency measure in more salient region (foreground) while decreasing the average saliency measure in the non-salient region (background). Implementation results of our method shows the merits of this approach with other competing methods.

关键词： Non-photorealistic rendering Saliency image Abstraction Guided Filter

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3D Video Spatiotemporal Multiple Description Coding Considering Region of Interest 15

3D Video Spatiotemporal Multiple Description Coding Consider...

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15th International Joint conference on computer vision, Imaging and computer graphics theory and Applications (VISIGRAPP) / 15th International conference on computer vision theory and Applications (VISAPP)

作者： Rahimi, Ehsan Joslin, Chris Carleton Univ Dept Syst & Comp Engn 1125 Colonel By Dr Ottawa ON Canada

ISBN: (纸本)9789897584022

3D video applications are being more favourable for observers as their requirements to receive and display 3D videos become more available recently. therefore the demand for more processing power and bandwidth is increasing to stream and display 3D multimedia services in either the wired or wireless networks. Since channel failure has been always as an integral part of communication between a receiver and transmitters, a robust method of video streaming is always a hot topic for researchers. To make robustness against failure more stronger, it needs to increase redundancies however it destroys the coding and compressing efficiency. therefore there is a trade-off problem between the coding efficiency and robustness of the stream. Among different methods of reliable video streaming, this paper introduces a new reliable 3D video streaming using hybrid multiple description coding. the proposed multiple description coding creates 3D video descriptions identifying interesting objects of the scene. To this end, a map for the region of interest is extracted from the depth map image first with a not complex algorithm compared to the available machine learning algorithm. Having realized region of interest, the proposed hybrid multiple description coding algorithm creates the descriptions for the color video using the advantages of both spatial and temporal multiple description coding methods;To this end, a non-identical decimation method concerning the identified objects assigns more bandwidth to those objects;second, background quality is improved with the temporal information. this way, first, the proposed method provides better visual performance as the human eye is more sensitive to objects than it is to pixels;second, the background is reconstructed with higher quality as it usually has a low movement and temporal information is a better choice to estimate the lost information. the objective test results verify the fact that the proposed method provides an improved perfo

关键词： 3D Video Stereoscopic Video Dolor image Depth Map image Multiple Descriotion Coding Temopral MDC Spatial MDC Hybrid MDC Reliable Multimedia Streaming Region of Interest

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Accelerating Applications using GPUs on Embedded Systems and Mobile Devices

Accelerating Applications using GPUs on Embedded Systems and...

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15th IEEE International conference on High Performance Computing and Communications (HPCC) /11th IEEE/IFIP International conference on Embedded and Ubiquitous Computing (EUC)

作者： Huang, Miaoqing Lai, Chenggang Univ Arkansas Dept Comp Sci & Comp Engn Fayetteville AR 72701 USA

ISBN: (纸本)9780769550886

graphics processing units (GPUs) are capable of achieving remarkable performance improvements for a broad range of applications. However, they have not been widely adopted in embedded systems and mobile devices as accelerators mainly due to their relatively higher power consumption compared with embedded microprocessors. In this work, we conduct a comprehensive analysis regarding the feasibility and potential of accelerating applications using GPUs in low-power domains. We use two different categories of benchmarks: (1) the Level 3 BLAS subroutines, and (2) the computer vision algorithms, i.e., mean shift image segmentation and scale-invariant feature transform (SIFT). We carried out our experiments on the Nvidia CARMA development kit, which consists of a Nvidia Tegra 3 quad-core CPU and a Nvidia Quadro 1000M GPU. It is found that the GPU can deliver a remarkable performance speedup compared with the CPU while using a significantly less energy for most benchmarks. Further we propose a hybrid approach to developing applications on platform with GPU accelerators. this approach optimally distributes workload between the parallel GPU and the sequential CPU to achieve the best performance while using the least energy.

关键词： Embedded systems Mobile devices graphics processing Unit central processing units GRAPPER PICK UP Accelerators acceleration comprehensive analysis images computer vision Workload optimum performance BENCHMARKS

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Adaptive nonlinear image denoising and restoration using a cooperative Bayesian estimation approach

Adaptive nonlinear image denoising and restoration using a c...

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6th indian conference on computer vision, graphics and image processing

作者： Mishra, Akshaya K. Wong, Alexander Clausi, David. A. Fieguth, Paul. W.

ISBN: (纸本)9781424442195

A novel nonlinear cooperative approach to image denoising and restoration is presented. Samples from the image field with similar characteristics are first grouped into clusters by first performing image decomposition based on the Mumford-Shah model using a total variational framework and performing fuzz), c-means clustering within each image partition. Samples within each cluster are then aggregated using an cooperative Bayesian estimation method based on information from all the samples to provide a nonlinear estimate of the original image. the proposed method exploits information redundancy within each cluster to denoise and restore the original image. Furthermore, the proposed cooperative Bayesian estimation method is capable of suppressing noise and reducing image degradation while preserving image detail by utilizing intra-cluster statistics. the experimental results using different types of images demonstrate that the proposed algorithm provides state-of-the-art image denoising performance in terms of both peak signal-to-noise ratio (PSNR) and subjective visual quality

关键词： Bayesian networks

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SpoofNET: Resolving Facial Makeup based Spoofs 11

SpoofNET: Resolving Facial Makeup based Spoofs

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11th indian conference on computer vision, graphics and image processing (ICVGIP)

作者： Bhattacharjee, Avishek Banerjee, Samik Das, Sukhendu Indian Inst Technol Madras Chennai 600036 Tamil Nadu India

ISBN: (纸本)9781450366151

Face Recognition (FR) under adversarial conditions has been a big challenge for researchers in the computer vision and Machine Learning communities in the recent past. Most of state-of-the-art face recognition systems have been designed to overcome degradations in a face due to variations in pose, illumination, contrast, resolution, along with blur. However, interestingly none have addressed the fascinating issue of makeup as a spoof attack, which drastically changes the appearance of a face, making it difficult for even humans to detect and identify the impostor. In this paper, we propose a novel multi-component deep convolutional neural network (CNN) based architecture which performs the complex task of makeup removal from a disguised face, to reveal the original mugshot image of the impostor (i.e. without makeup). the proposed network also performs the hard tasks of FR on a disguised face in addition to recognition of identity and generation of the face of the spoofed target, by minimizing a novel multi-component objective function. Comparison of performance with a few recent state-of-the-art methods of FR over three benchmark datasets reveals the superiority of our proposed method for both synthesis as well as recognition (FR) tasks.

关键词： Face recognition

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Multimodal Egocentric Activity Recognition Using Multi-stream CNN 11

Multimodal Egocentric Activity Recognition Using Multi-strea...

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11th indian conference on computer vision, graphics and image processing (ICVGIP)

作者： Imran, Javed Raman, Balasubramanian Indian Inst Technol Roorkee Dept Comp Sci & Engn Roorkee Uttar Pradesh India

ISBN: (纸本)9781450366151

Egocentric activity recognition (EAR) is an emerging area in the field of computer vision research. Motivated by the current success of Convolutional Neural Network (CNN), we propose a multi-stream CNN for multimodal egocentric activity recognition using visual (RGB videos) and sensor stream (accelerometer, gyroscope, etc.). In order to effectively capture the spatio-temporal information contained in RGB videos, two types of modalities are extracted from visual data: Approximate Dynamic image (ADI) and Stacked Difference image (SDI). these image-based representations are generated both at clip level as well as entire video level, and are then utilized to finetune a pretrained 2D-CNN called MobileNet, which is specifically designed for mobile vision applications. Similarly for sensor data, each training sample is divided into three segments, and a deep 1D-CNN network is trained (corresponding to each type of sensor stream) from scratch. During testing, the softmax scores of all the streams (visual + sensor) are combined by late fusion. the experiments performed on multimodal egocentric activity dataset demonstrates that our proposed approach can achieve state-of-the-art results, outperforming the current best handcrafted and deep learning based techniques.

关键词： Egocentric Activity Recognition Convolutional Neural Network Dynamic image Stacked Difference image Multimodal Fusion

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A Context Dependent Fragile Watermarking Scheme for Tamper Detection from Demosaicked Color images 16

A Context Dependent Fragile Watermarking Scheme for Tamper D...

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10th indian conference on computer vision, graphics and image processing (ICVGIP)

作者： Manikandan, V. M. Masilamani, V. Indian Inst Informat Technol Design & Mfg Kanchee Madras 600127 Tamil Nadu India

ISBN: (纸本)9781450347532

Fragile watermarking schemes are very common in practice for tamper detection and image authentication. In this paper, we propose a new fragile watermarking scheme to detect common image tampering operations such as copy and paste attack and image splicing attack from color images. the proposed scheme is intended to do the watermarking with an image dependent authentication code during color image demosaicking procedure. We propose a new method to generate almost unique authentication code from an image by comparing RGB color components of the pixels. In the proposed scheme, every pixel will be watermarked with an encrypted authentication code derived from the same pixel. To embed the watermark a new method has been proposed in this paper, where the color filter array sampled components will not be considered during watermarking, and only the rebuilt color component values of every pixel will be modified according to the authentication code. the experimental study shows that the proposed watermarking scheme produces images with better visual quality as compared to the state-of-the-art, and is capable of detecting both copy and paste attacks and image splicing attacks more accurately than the existing schemes.

关键词： fragile watermarking image demosaicking tamper detection authentication code

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Intelligent visibility-based 3D scene processing techniques for computer games

Intelligent visibility-based 3D scene processing techniques ...

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15th International conference on computer graphics and vision, GraphiCon 2005

作者： Plemenos, Dimitri Grasset, Jérôme Jaubert, BenoÎt Tamine, Karim MSI laboratory University of Limoges 83 rue d'Isle 87000 Limoges France Institut d'Ingénerie Informatique de Limoges High School of Computer Science Engineering Rue Sante-Anne Limoges France

In this paper we present intelligent visibility-based techniques allowing efficient processing of 3D scenes in order to be used in real time in computer games. the presented techniques allow real time use of 3D scenes either by simplifying the scene models (by suppressing useless details or by using improved image-based modelling) or by off-line automatic camera path pre-computation allowing fast exploration of the game environment.

关键词： computer games

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