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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"

共 1471 条记录，以下是601-610 订阅

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

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

引用

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

引用

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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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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Preface

Communications in Computer and Information Science

引用

Communications in computer and Information Science 2018年 841卷 VI页

作者： Rameshan, Renu Arora, Chetan Roy, Sumantra Dutta Indian Institute of Technology Mandi MandiHimachal Pradesh India Indraprastha Institute of Information Technology New Delhi India Indian Institute of Technology New Delhi India

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Analyzing object categories via novel category ranking measures defined on visual feature embeddings 16

Analyzing object categories via novel category ranking measu...

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

作者： Sarvadevabhatla, Ravi Kiran Meesala, Raviteja Hegde, Manjunath Babu, Venkatesh R. Indian Inst Sci Dept Computat & Data Sci Video Analyt Lab Bangalore Karnataka India

ISBN: (纸本)9781450347532

Visualizing 2-D/3-D embeddings of image features can help gain an intuitive understanding of the image category landscape. However, popular visualization methods of visualizing such embeddings (e.g. color-coding by category) are impractical when the number of categories is large. To address this and other shortcomings, we propose novel quantitative measures defined on image feature embeddings. Each measure produces a ranked ordering of the categories and provides an intuitive vantage point from which to view the entire set of categories. As an experimental testbed, we use deep features obtained from category-epitomes, a recently introduced minimalist visual representation, across 160 object categories. We embed the features in a visualization friendly yet similarity-preserving 2-D manifold and analyze the inter/intra-category distributions of these embeddings using the proposed measures. Our analysis demonstrates that the category ordering methods enable new insights for the domain of large-category object representations. Moreover, our ordering measure approach is general in nature and can be applied to any feature-based representation of categories.

关键词： Visualization

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Towards Quantifying the Amount of Uncollected Garbage through image Analysis 16

Towards Quantifying the Amount of Uncollected Garbage throug...

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

作者： Suresh, Susheel Sharma, Tarun Prashanth, T. K. Subramaniam, V Sitaram, Dinkar Nirupama, M. PES Inst Technol Dept Comp Sci Bengaluru 560085 India

ISBN: (纸本)9781450347532

Civic authorities in many indian cities have a tough time in garbage collection and as a result there is a pile up of garbage in the cities. In order to manage the situation, it is first required to be able to quantify the issue. In this paper, we address the problem of quantification of garbage in a dump using a two step approach. In the first step, we build a mobile application that allows citizens to capture images of garbage and upload them to a server. In the second step, back-end performs analysis on these images to estimate the amount of garbage using computer vision techniques. Our approach to volume estimation uses multiple images of the same dump (provided by the mobile application) from different perspectives, segments the dump from the background, reconstructs a three dimensional view of the dump and then estimates its volume. Using our novel pipeline, our experiments indicate that with 8 different perspectives, we are able to achieve an accuracy of about 85 % for estimating the volume.

关键词： Automatic Segmentation and 3D Reconstruction Segmentation using Deep Learning Structure from Motion Volume Estimation of Garbage Dumps

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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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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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Depth Estimation from Single image using Machine Learning Techniques 16

Depth Estimation from Single Image using Machine Learning Te...

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

作者： Chahal, Nidhi Pippal, Meghna Chaudhury, Santanu Indian Inst Technol Delhi India Cent Elect Engn Res Inst Pilani Pilani Rajasthan India

ISBN: (纸本)9781450347532

In this paper, the problem of depth estimation from single monocular image is considered. The depth cues such as motion, stereo correspondences are not present in single image which makes the task more challenging. We propose a machine learning based approach for extracting depth information from single image. The deep learning is used for extracting features, then, initial depths are generated using manifold learning in which neighborhood preserving embedding algorithm is used. Then, fixed point supervised learning is applied for sequential labeling to obtain more consistent and accurate depth maps. The features used are initial depths obtained from manifold learning and various image based features including texture, color and edges which provide useful information about depth. A fixed point contraction mapping function is generated using which depth map is predicted for new structured input image. The transfer learning approach is also used for improvement in learning in a new task through the transfer of knowledge from a related task that has already been learned. The predicted depth maps are reliable, accurate and very close to ground truth depths which is validated using objective measures: RMSE, PSNR, SSIM and subjective measure: MOS score.

关键词： Monocular manifold sequential labeling

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