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检索条件"任意字段=10th Indian Conference on Computer Vision, Graphics and Image Processing, ICVGIP 2016"

共 143 条记录，以下是11-20 订阅

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Efficient Adaptive Weighted Minimization for Compressed Sensing Magnetic Resonance image Reconstruction 16

Efficient Adaptive Weighted Minimization for Compressed Sens...

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

作者： Datta, Sumit Deka, Bhabesh Tezpur Univ Dept ECE CVIP Lab Tezpur 784028 Assam India

ISBN: (纸本)9781450347532

Compressed sensing magnetic resonance imaging (CSMRI) have demonstrated that it is possible to accelerate MRI scan time by reducing the number of measurements in the k-space without significant loss of anatomical details. the number of k-space measurements is roughly proportional to the sparsity of the MR signal under consideration. Recently, a few works on CSMRI have revealed that the sparsity of the MR signal can be enhanced by suitable weighting of different regularization priors. In this paper, we have proposed an efficient adaptive weighted reconstruction algorithm for the enhancement of sparsity of the MR image. Experimental results show that the proposed algorithm gives better reconstructions with less number of measurements without significant increase of the computational time compared to existing algorithms in this line.

关键词： Magnetic resonance imaging compressed sensing l(1)-norm total variation regularization image reconstruction

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Bishnupur Heritage image Dataset (BHID): A resource for various computer vision applications 16

Bishnupur Heritage Image Dataset (BHID): A resource for vari...

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

作者： Ghorai, Mrinmoy Purkait, Pulak Santra, Sanchayan Samanta, Soumitra Chanda, Bhabatosh Indian Stat Inst Kolkata India Adelaide Univ Adelaide SA Australia

ISBN: (纸本)9781450347532

Bishnupur is an attractive tourist place in West Bengal, India and is known for its terracotta temples. the place is one of the prospective candidates to be included in the list of UNESCO World Heritage sites. We intend to preserve this heritage site digitally and also to present some virtual interaction for the tourist and researchers. In this paper, we present an image dataset of different temples (namely, Jor Bangla, Kalachand, Madan Mohan, Radha Madhav, Rasmancha, Shyamrai and Nandalal) in Bishnupur for evaluating different types of computer vision and image processing algorithms (like 3D reconstruction, image inpainting, texture classification and content specific image retrieval). the dataset is captured using four different cameras with different parameter settings. Some datasets are extracted and earmarked for certain applications such as texture classification, image inpainting and content specific image retrieval. Example results of baseline methods are also shown for these applications. thus we evaluate the usefulness of this dataset. To the best of our knowledge, probably this is the first attempt of combined dataset for evaluating various types of problems for a heritage site in India.

关键词： Heritage data SFM image inpainting temple texture

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Compensating for Large In-Plane Rotations in Natural images 16

Compensating for Large In-Plane Rotations in Natural Images

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

作者： Boominathan, Lokesh Srinivas, Suraj Babu, R. Venkatesh Indian Inst Sci Video Analyt Lab Bangalore 560012 Karnataka India

ISBN: (纸本)9781450347532

Rotation invariance has been studied in the computer vision community primarily in the context of small in-plane rotations. this is usually achieved by building invariant image features. However, the problem of achieving invariance for large rotation angles remains largely unexplored. In this work, we tackle this problem by directly compensating for large rotations, as opposed to building invariant features. this is inspired by the neuro-scientific concept of mental rotation, which humans use to compare pairs of rotated objects. Our contributions here are three-fold. First, we train a Convolutional Neural Network (CNN) to detect image rotations. We find that generic CNN architectures are not suitable for this purpose. To this end, we introduce a convolutional template layer, which learns representations for canonical 'unrotated' images. Second, we use Bayesian Optimization to quickly sift through a large number of candidate images to find the canonical 'unrotated' image. third, we use this method to achieve robustness to large angles in an image retrieval scenario. Our method is task-agnostic, and can be used as a pre-processing step in any computer vision system.

关键词： Deep neural networks image retrieval rotation invariance Bayesian optimization

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Ghosting Free HDR for Dynamic Scenes via Shift-maps 16

Ghosting Free HDR for Dynamic Scenes via Shift-maps

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

作者： Prabhakar, K. Ram Babu, R. Venkatesh Indian Inst Sci Dept Computat & Data Sci Bangalore Karnataka India

ISBN: (纸本)9781450347532

Given a set of sequential exposures, High Dynamic Range imaging is a popular method for obtaining high-quality images for fairly static scenes. However, this typically suffers from ghosting artifacts for scenes with significant motion. Also, existing techniques cannot handle heavily saturated regions in the sequence. In this paper, we propose an approach that handles both the issues mentioned above. We achieve robustness to motion (both object and camera) and saturation via an energy minimization formulation with spatio-temporal constraints. the proposed approach leverages information from the neighborhood of heavily saturated regions to correct such regions. the experimental results demonstrate the superiority of our method over state-of-the-art techniques for a variety of challenging dynamic scenes.

关键词： Exposure Fusion High Dynamic Range imaging

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TraCount: A Deep Convolutional Neural Network for Highly Overlapping Vehicle Counting 16

TraCount: A Deep Convolutional Neural Network for Highly Ove...

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

作者： Surya, Shiv Babu, Venkatesh R. Indian Inst Sci Bangalore Karnataka India

ISBN: (纸本)9781450347532

We propose a novel deep framework, TraCount, for highly overlapping vehicle counting in congested traffic scenes. TraCount uses multiple fully convolutional(FC) sub-networks to predict the density map for a given static image of a traffic scene. the different FC sub-networks provide a range in size of receptive fields that enable us to count vehicles whose perspective effect varies significantly in a scene due to the large visual field of surveillance cameras. the predictions of different FC sub-networks are fused by weighted averaging to obtain a final density map. We show that TraCount outperforms the state of the art methods on the challenging TRANCOS dataset that has a total of 46796 vehicles annotated across 1244 images.

关键词： Convolutional neural networks deep learning vehicle counting

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

Overlapping Cell Nuclei Segmentation in Microscopic Images U...

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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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A STRATIFIED REGISTRATION FRAMEWORK FOR DSA ARTIFACT REDUCTION USING RANDOM WALKER 16

A STRATIFIED REGISTRATION FRAMEWORK FOR DSA ARTIFACT REDUCTI...

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

作者： Sundarapandian, Manivannan Kalpathi, Ramakrishnan Siemens Healthcare Private Ltd 84 Hosur Rd Bangalore 560100 Karnataka India Indian Inst Sci Dept Elect Engn Bangalore 560012 Karnataka India

ISBN: (纸本)9781450347532

In Digital Subtraction Angiography (DSA), non-rigid registration of the mask and contrast images to reduce the motion artifacts is a challenging problem. In this paper, we have proposed a novel stratified registration framework for DSA artifact reduction. We use quad-trees to generate the non-uniform grid of control points and obtain the sub-pixel displacement offsets using Random Walker (RW). We have also proposed a sequencing logic for the control points and an incremental LU decomposition approach that enables reuse of the computations in the RW step. We have tested our approach using clinical data sets, and found that our registration framework has performed comparable to the graph-cuts (at the same partition level), in regions wherein 95% artifact reduction was achieved. the optimization step achieves a speed improvement of 4.2 times with respect to graph-cuts.

关键词： image Registration Random Walker DSA quad-trees

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Hierarchical Spectral Clustering based Large Margin Classification of Visually Correlated Categories 16

Hierarchical Spectral Clustering based Large Margin Classifi...

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

作者： Bose, Digbalay Chaudhuri, Subhasis IBM Res Bangalore Karnataka India Indian Inst Technol Dept Elect Engn Bombay Maharashtra India

ISBN: (纸本)9781450347532

Object recognition is one of the challenging tasks in computer vision and the problem becomes increasingly difficult when the image categories are visually correlated among themselves i.e. they are visually similar and only fine differences exist among the categories. this paper has a two-fold objective which involves organization of the image categories in a hierarchical tree like structure using self tuning spectral clustering for exploiting the correlations among them. the organization phase is followed by a node specific large margin nearest neighbor classification scheme, where a Mahalnobis distance metric is learnt for each non-leaf node. Further a procedure for hyperparameters selection has been discussed w.r.t two strategies i.e. grid search and Bayesian optimization. the proposed algorithm's effectiveness is tested on selected classes of the popular imagenet dataset.

关键词： Object recognition Visually correlated categories Large margin nearest neighbor classification Self Tuning Spectral Clustering Hierarchical Organization

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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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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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