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

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How Much Can A Gaussian Smoother Denoise? 16

How Much Can A Gaussian Smoother Denoise?

引用

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

作者： Gubbi, Sagar Venkatesh Gupta, Ashutosh Seelamantula, Chandra Sekhar Indian Inst Sci Dept Elect Commun Engn Bangalore 560012 Karnataka India Indian Space Res Org Ahmadabad 380058 Gujarat India Indian Inst Sci Dept Elect Engn Bangalore 560012 Karnataka India

ISBN: (纸本)9781450347532

Recently, a suite of increasingly sophisticated methods have been developed to suppress additive noise from images. Most of these methods take advantage of sparsity of the underlying signal in a specific transform domain to achieve good visual or quantitative results. These methods apply relatively complex statistical modelling techniques to bifurcate the noise from the signal. In this paper, we demonstrate that a spatially adaptive Gaussian smoother could be a very effective solution to the image denoising problem. To derive the optimal parameter estimates for the Gaussian smoothening kernel, we derive and deploy a surrogate of the mean squared error (MSE) risk similar to the Stein's estimator for Gaussian distributed noise. However, unlike the Stein's estimator or its counterparts for other noise distributions, the proposed generic risk estimator (GenRE) uses only first- and second-order moments of the noise distribution and is agnostic to the exact form of the noise distribution. By locally adapting the parameters of the Gaussian smoother, we obtain a denoising function that has a denoising performance (quantified by the peak signal-to-noise ratio (PSNR)) that is competitive to far more sophisticated methods reported in the literature. To avail the parallelism offered by the proposed method, we also provide a graphics processing unit (GPU) based implementation.

关键词： image denoising Gaussian smoothing Stein's lemma generic risk estimation spatially varying smoothers graphics processing unit (GPU)

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Overlapping Cell Nuclei Segmentation in Microscopic images Using Deep Belief Networks 16

Overlapping Cell Nuclei Segmentation in Microscopic Images U...

引用

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

作者： Duggal, Rahul Gupta, Anubha Gupta, Ritu Wadhwa, Manya Ahuja, Chirag Indraprastha Inst Informat Technol Delhi Dept ECE SBILab New Delhi India AIIMS Dr BRA IRCH Lab Oncol Unit Delhi India Inst Informat Technol Delhi Dept CSE New Delhi India

ISBN: (纸本)9781450347532

This paper proposes a method for segmentation of nuclei of single/isolated and overlapping/touching immature white blood cells from microscopic images of B-Lineage acute lymphoblastic leukemia (ALL) prepared from peripheral blood and bone marrow aspirate. We propose deep belief network approach for the segmentation of these nuclei. Simulation results and comparison with some of the existing methods demonstrate the efficacy of the proposed method.

关键词： Overlapping nuclei segmentation B-ALL Deep Belief Network Machine Learning

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Robust Pedestrian Tracking using improved Tracking-Learning-Detection algorithm 16

Robust Pedestrian Tracking using improved Tracking-Learning-...

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

作者： Verma, Ritika Sreedevi, Indu Delhi Technol Univ Delhi India

ISBN: (纸本)9781450347532

Manual analysis of pedestrians for surveillance of large crowds in real time applications is not practical. Tracking-Learning-Detection suggested by Kalal , Mikolajczyk and Matas [1] is one of the most prominent automatic object tracking system. TLD can track single object and can handle occlusion and appearance change but it suffers from limitations .In this paper, tracking of multiple objects and estimation of their trajectory is suggested using improved TLD. Feature tracking is suggested in place of grid based tracking to solve the limitation of tracking during out of plane rotation .This also leads to optimization of algorithm. Proposed algorithm also achieves auto-initialization with detection of pedestrians in the first frame which makes it suitable for real time pedestrian tracking.

关键词： Tracking-Learning-Detection Pedestrian tracking Visual tracking

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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

引用

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 ...

引用

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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