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检索条件"任意字段=Proceedings of the Fourteenth Indian Conference on Computer Vision, Graphics and Image Processing"

共 1496 条记录，以下是601-610 订阅

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Towards Semantic Visual Representation: Augmenting image Representation with Natural Language Descriptors 16

Towards Semantic Visual Representation: Augmenting Image Rep...

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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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Deep image Inpainting with Region Prediction at Hierarchical Scales 16

Deep Image Inpainting with Region Prediction at Hierarchical...

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

作者： Chakraborty, Souradeep Kundu, Jogendra Nath Babu, R. Venkatesh Indian Inst Sci Dept Computat & Data Sci Bangalore Karnataka India

ISBN: (纸本)9781450347532

In this paper, we propose a CNN based method for image inpainting, which utilizes the inpaintings generated at different hierarchical resolutions. Firstly, we begin with the prediction of the missing image region with larger contextual information at the lowest resolution using deconv layers. Next, we refine the predicted region at greater hierarchical scales by imposing gradually reduced contextual information surrounding the predicted region by training different CNNs. Thus, our method not only utilizes information from different hierarchical resolutions but also intelligently leverages the context information at different hierarchy to produce better inpainted image. The individual models are trained jointly, using loss functions placed at intermediate layers. Finally, the CNN generated image region is sharpened using the unsharp masking operation, followed by intensity matching with the contextual region, to produce visually consistent and appealing inpaintings with more prominent edges. Comparison of our method with well-known inpainting methods, on the Caltech 101 objects dataset, demonstrates the quantitative and qualitative strengths of our method over the others.

关键词： image inpainting context hierarchical scales image sharpening intensity matching

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Multi-slice Tomographic Reconstruction: To Couple or Not to Couple 16

Multi-slice Tomographic Reconstruction: To Couple or Not to ...

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

作者： Gopal, Preeti Chandran, Sharat Svalbe, Imants Rajwade, Ajit Indian Inst Technol Dept Comp ViGIL Bombay Maharashtra India IITB Monash Res Acad Bombay Maharashtra India Monash Univ Dept Phys & Astron Clayton Vic Australia

ISBN: (纸本)9781450347532

Recent work in tomography focuses on algorithms that enable faster and more accurate reconstruction from as few measurements as possible. We review the advantage of jointly reconstructing multiple slices and show that joint reconstruction may suffer in the presence of adjacent dissimilar slices. This gives rise to the need to detect similarity or dissimilarity of unknown images before performing joint reconstruction. We propose a method to detect 'similar' slices directly from their tomographic measurements and juxtapose these similar slices. Since the images themselves are not available by definition, we compute similarity between slices based on image moments;these in turn are estimated in a novel way from Radon projection moments. A segmented least squares algorithm is then designed to couple only similar slices. Our results confirm the benefit of this method for tomographic reconstruction.

关键词： Compressive sensing Radon projection moments image moments tomographic reconstruction

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Automatic Video Matting through Scribble Propagation 16

Automatic Video Matting through Scribble Propagation

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

作者： Sonane, Bhoomika Ramakrishnan, Sainandan Raman, Shanmuganathan IIT Gandhinagar Ahmadabad Gujarat India VJTI Bombay Maharashtra India

ISBN: (纸本)9781450347532

Video matting is an extension of image matting and is used to extract the foreground matte from an arbitrary background of every frame in a video sequence. An automatic scribbling approach based on the relative motion of the foreground object with respect to the background in a video is introduced for video matting. The proposed scribble propagation and the subsequent isolation of foreground and background is much more intuitive than the conventional trimap propagation approach used for video matting. Alpha maps are propagated according to the optical flow estimated from the consecutive frames to get a preliminary estimate of the foreground and background in the following frame. Accurate scribbles are placed near the boundary of the foreground region for re fining the scribbled image with the help of morphological operations. We show that a high quality matte of foreground object can be obtained using a state-of-the-art image matting technique. We show that the results obtained using the proposed method are accurate and comparable with that of other state-of-the-art video matting techniques.

关键词： Video matting Optical flow Computational photography

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Robust Segmentation of Corneal Fibers from Noisy images 16

Robust Segmentation of Corneal Fibers from Noisy Images

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

作者： Chen, Jia Jester, James Gopi, M. Univ Calif Irvine Dept Comp Sci Irvine CA 92697 USA Univ Calif Irvine Sch Med Irvine CA 92717 USA

ISBN: (纸本)9781450347532

Corneal collagen structure, which plays an important role in determining visual acuity, has drawn a lot of research attention to exploring its geometric properties. Advancement of nonlinear optical (NLO) imaging provides a potential way for capturing fiber-level structure of cornea, however, the artifacts introduced by the NLO imaging process make image segmentation on such images a bottleneck for further analysis. Especially, the existing methods fail to preserve the branching points which are important for mechanical analysis. In this paper, we propose a hybrid image segmentation method, which integrates seeded region growing and iterative voting. Results show that our algorithm outperforms state-of-the-art techniques in segmenting fibers from background while preserving branching points. Finally, we show that, based on the segmentation result, branching points and the width of fibers can be determined more accurately than the other methods, which is critical for mechanical analysis on corneal structure.

关键词： image Segmentation Branching Point Detection Linear Structure Extraction

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Informed Multimodal Latent Subspace Learning via Supervised Matrix Factorization 16

Informed Multimodal Latent Subspace Learning via Supervised ...

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

作者： Gaurav, Ramashish Verma, Mridula Shukla, K. K. BHU Indian Inst Technol Varanasi Uttar Pradesh India

ISBN: (纸本)9781450347532

Matrix factorization technique has been widely used as a popular method to learn a joint latent-compact subspace, when multiple views or modals of objects (belonging to single-domain or multiple-domain) are available. Our work confronts the problem of learning an informative latent subspace by imparting supervision to matrix factorization for fusing multiple modals of objects, where we devise simpler supervised additive updates instead of multiplicative updates, thus scalable to large scale datasets. To increase the classification accuracy we integrate the label information of images with the process of learning a semantically enhanced subspace. We perform extensive experiments on two publicly available standard image datasets of NUS WIDE and compare the results with state-of-the-art subspace learning and fusion techniques to evaluate the efficacy of our framework. Improvement obtained in the classification accuracy confirms the effectiveness of our approach. In essence, we propose a novel method for supervised data fusion thus leading to supervised subspace learning.

关键词： image Classification Joint Subspace Learning Supervised Matrix Factorization

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Generating Synthetic Handwriting using n-gram letter glyphs 16

Generating Synthetic Handwriting using n-gram letter glyphs

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

作者： Dey, Arka Ujjal Harit, Gaurav Indian Inst Technol Jodhpur Old Residency Rd Jodhpur Rajasthan India

ISBN: (纸本)9781450347532

We propose a framework for synthesis of natural semi cursive handwritten Latin script that can find application in text personalization, or in generation of synthetic data for recognition systems. Our method is based on the generation of synthetic n-gram letter glyphs and their subsequent concatenation. We propose a non-parametric data driven generation scheme that is able to mimic the variation observed in handwritten glyph samples to synthesize natural looking synthetic glyphs. These synthetic glyphs are then stitched together to form complete words, using a spline based concatenation scheme. Further, as a refinement, our method is able to generate pen-lifts, giving our results a natural semi cursive look. Through subjective experiments and detailed analysis of the results, we demonstrate the effectiveness of our formulation in being able to generate natural looking synthetic script.

关键词： HandWriting Synthesis Gaussian Process n-gram

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Event Geo-Localization and Tracking From Crowd-Sourced Video Metadata 16

Event Geo-Localization and Tracking From Crowd-Sourced Video...

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

作者： More, Amit Chaudhuri, Subhasis Indian Inst Technol Dept Elect Engn Bombay Maharashtra India

ISBN: (纸本)9781450347532

We propose a novel technique for event geo-localization (i.e. 2-D location of the event on the surface of the earth) from the sensor metadata of crowd-sourced videos collected from smartphone devices. With the help of sensors available in the smartphone devices, such as digital compass and GPS receiver, we collect metadata information such as camera viewing direction and location along with the video. The event localization is then posed as a constrained optimization problem using available sensor metadata. Our results on the collected experimental data shows correct localization of events, which is particularly challenging for classical vision based methods because of the nature of the visual data. Since we only use sensor metadata in our approach, computational overhead is much less compared to what would be if video information is used. At the end, we illustrate the benefits of our work in analyzing the video data from multiple sources through geo-localization.

关键词： Event localization Smartphone Digital Compass Optimization GPS

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Enhancement of High Dynamic Range images Using Variational Calculus Regularizer with Stochastic Resonance 16

Enhancement of High Dynamic Range Images Using Variational C...

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

作者： Kumar, Sumit Jha, Rajib Kumar Indian Inst Technol Patna Patna Bihar India

ISBN: (纸本)9781450347532

While capturing pictures by a simple camera in a scene with the presence of harsh or strong lighting like a full sunny day, we often find loss of highlight detail information (overexposure) in the bright regions and loss of shadow detail information (underexposure) in dark regions. In this manuscript, a classical method for retrieval of minute information from the high dynamic range image has been proposed. Our technique is based on variational calculus and dynamic stochastic resonance (DSR). We use a regularizer function, which has been added in order to optimise the correct estimation of the lost details from the overexposed or underexposed region of the image. We suppress the dynamic range of the luminance image by attenuating large gradient with the large magnitude and low gradient with low magnitude. At the same time, dynamic stochastic resonance (DSR) has been used to improve the underexposed region of the image. The experimental results of our proposed technique are capable of enhancing the quality of images in both overexposed and underexposed regions. The proposed technique is compared with most of the state-of-the-art techniques and it has been observed that the proposed technique is better or at most comparable to the existing techniques.

关键词： Dynamic stochastic resonance (DSR) wavelet variational calculus regularizer gradient tone mapping

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Feature-Preserving 3D Fluorescence image Sequence Denoising 16

Feature-Preserving 3D Fluorescence Image Sequence Denoising

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

作者： Bhujle, Hemalata SDM Coll Engn & Technol Dept Elect & Commun Engn Dharwad Karnataka India

ISBN: (纸本)9781450347532

In this paper feature-preserving denoising scheme for fluorescence video microscopy is presented. Fluorescence image sequences comprise of edges and fine structures with fast moving objects. Improving signal to noise ratio (SNR) while preserving structural details is a difficult task for these image sequences. Few existing denoising techniques result in over smoothing these image sequences while others fail due to inappropriate implementation of motion estimation and compensation steps. In this paper we use nonlocal means (NLM) video denoising algorithm as to avoid motion estimation and compensation steps. The proposed shot boundary detection technique pre-processes the sequence systematically and accurately to form different shots with content-wise similar frames. To preserve the edges and fine structural details in the image sequences we modify the weighing term of NLM filter. Further, to accelerate the denoising process, separable non-local means filter is implemented for video sequences. We compare the results with existing fluorescence video denoising techniques and show that the proposed method not only preserves the edges and small structural details more efficiently, also reduces the computational time. Efficacy of the proposed algorithm is evaluated quantitatively and qualitatively with PSNR and vision perception.

关键词： Non-local means fluorescence microscopy

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