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

共 1497 条记录，以下是1311-1320 订阅

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image-Based Multiscale Shape Description Using Gaussian Filter

Image-Based Multiscale Shape Description Using Gaussian Filt...

引用

indian conference on computer vision, graphics & image processing (ICVGIP)

作者： Cem Direkoglu Mark S. Nixon School of Electronics and Computer Science University of Southampton Southampton UK

In shape recognition, a multiscale description provides more information about the object, increases discrimination power and immunity to noise. In this paper, we develop a new multiscale Fourier-based object description in 2-D space using a low-pass Gaussian filter (LPGF) and a high-pass Gaussian filter (HPGF), separately. Using the LPGF, at different scales, represents the inner and central part of an object more than the boundary. On the other hand using the HPGF, at different scales, represents the boundary and exterior parts of an object more than the central part. Our algorithms are also organized to achieve size, translation and rotation invariance. Evaluation indicates that representing the boundary and exterior parts more than the central part using the HPGF performs better than the LPGF based multiscale representation, and in comparison to Zernike moments and elliptic Fourier descriptors with respect to increasing noise.

关键词： Shape Filters Multi-stage noise shaping Cascading style sheets computer vision Performance evaluation Fourier transforms computer graphics image processing Information filtering

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Parametric Video Compression Scheme Using AR Based Texture Synthesis

Parametric Video Compression Scheme Using AR Based Texture S...

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indian conference on computer vision, graphics & image processing (ICVGIP)

作者： Aditya Khandelia Saurabh Gorecha Brejesh Lall Santanu Chaudhury Mona Mathur Department of Electrical Engineering Indian Institute of Technology New Delhi India

In this paper a video coding scheme based on parametric compression of texture is proposed. Each macro block is characterized either as an edge block, or as a non edge block containing texture. The non edge blocks are coded by modeling them as an auto-regressive process (AR). By applying the AR model in spatio-temporal domain, we ensure both spatial as well as temporal consistency. Edge blocks are encoded using the standard H.264/AVC. The proposed algorithm achieves upto 54.52% more compression as compared to the standard H.264/AVC at similar visual quality.

关键词： Video compression image coding Synthesizers Redundancy Yarn Decoding Video coding Automatic voltage control Computational complexity computer vision

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A Novel Window-Based Corner Detection Algorithm for Gray-Scale images

A Novel Window-Based Corner Detection Algorithm for Gray-Sca...

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indian conference on computer vision, graphics & image processing (ICVGIP)

作者： Ambar Dutta Avijit Kar B.N. Chatterji Department of CSE Birla Institute of Technology and Science Kolkata India Department of CSE Jadavpur University Kolkata India Department of ECE B. P. Poddar Institute of Management and Technology Kolkata India

In computer vision, the corners of an object play an important role in shape representation and analysis. In this paper, we describe a new approach to corner detection in a digital image based on the assumption that corners are image points with high information content, and hence corners in an image exist in the regions having considerably high intensity variations. Consequently, a complex corner response function (CRF) is computed only within the regions with considerable high intensity variation instead of entire image reducing the computational cost of the whole procedure. Experiments are conducted with the help of a few images showed the efficiency of the technique, both in terms of execution time and false positive corners.

关键词： Detection algorithms Gray-scale Detectors computer vision image edge detection Shape image segmentation Performance evaluation Pixel image analysis

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Monocular Depth by Nonlinear Diffusion

Monocular Depth by Nonlinear Diffusion

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indian conference on computer vision, graphics & image processing (ICVGIP)

作者： Mariella Dimiccoli Jean-Michel Morel Philippe Salembier Dept. of Signal Theory and Com Technical University of Catalonia Barcelona Spain Dept. of Applied Mathematics Superior Normal School of Cachan Cachan France

Following the phenomenological approach of gestaltists, sparse monocular depth cues such as T- and X-junctions and the local convexity are crucial to identify the shape and depth relationships of depicted objects. According to Kanizsa, mechanisms called a modal and modal completion permit to transform these local relative depth cues into a global depth reconstruction. In this paper, we propose a mathematical and computational translation of gestalt depth perception theory, from the detection of local depth cues to their synthesis into a consistent global depth perception. The detection of local depth cues is built on the response of a line segment detector (LSD), which works in a linear time relative to the image size without any parameter tuning. The depth synthesis process is based on the use of a nonlinear iterative filter which is asymptotically equivalent to the Perona-Malik partial differential equation (PDE). Experimental results are shown on several real images and demonstrate that this simple approach can account a variety of phenomena such as visual completion, transparency and self-occlusion.

关键词： computer vision Shape image reconstruction Visual system computer graphics image processing Signal processing Mathematics Object recognition image segmentation

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Attention-Based Super Resolution from Videos

Attention-Based Super Resolution from Videos

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indian conference on computer vision, graphics & image processing (ICVGIP)

作者： Dileep Vaka P.J. Narayanan C.V. Jawahar Center for Visual Information Technology IIIT-Hyderabad India

A video from a moving camera produces different number of observations of different scene areas. We can construct an attention map of the scene by bringing the frames to a common reference and counting the number of frames that observed each scene point. Different representations can be constructed from this. The base of the attention map gives the scene mosaic. Super-resolved images of parts of the scene can be obtained using a subset of observations or video frames. We can combine mosaicing with super-resolution by using all observations, but the magnification factor will vary across the scene based on the attention received. The height of the attention map indicates the amount of super-resolution for that scene point. We modify the traditional super-resolution framework to generate a varying resolution image for panning cameras in this paper. The varying resolution image uses all useful data available in a video. We introduce the concept of attention-based super-resolution and give the modified framework for it. We also show its applicability on a few indoor and outdoor videos.

关键词： Videos Layout image resolution Strips Cameras computer vision computer graphics image processing Information technology image registration

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Unsupervised Segmentation of Retinal Blood Vessels Using a Single Parameter Vesselness Measure

Unsupervised Segmentation of Retinal Blood Vessels Using a S...

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indian conference on computer vision, graphics & image processing (ICVGIP)

作者： Nancy M. Salem Asoke K. Nandi Signal Processing and Communications Group Department of Electrical Engineering and Electronics University of Liverpool UK

In this paper, a novel vesselness measure based on analysis of the Hessian matrix is presented. The larger eigenvalue of the Hessian matrix is used for vessel centerlines detection, while vessel orientations are estimated from the eigenvectors corresponding to the smaller eigenvalue. The vesselness measure combines information from vessel centerlines and orientations over scales to segment retinal blood vessels from colour fundus images. A publicly available dataset is used to evaluate the performance of our proposed method which has the advantage of being unsupervised and of using only one parameter.

关键词： Retina Blood vessels Biomedical imaging image segmentation Matched filters Pixel Eigenvalues and eigenfunctions image analysis Retinopathy Diabetes

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Explosion Simulation Using Compressible Fluids

Explosion Simulation Using Compressible Fluids

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indian conference on computer vision, graphics & image processing (ICVGIP)

作者： Abhinav Golas Akram Khan Prem Kalra Subodh Kumar Department of Computer Science Indian Institute of Technology New Delhi India

We propose a novel physically based method to simulate explosions and other compressible fluid phenomena. The method uses compressible Navier Stokes equations for modeling the explosion with a Semi-Lagrangian integration method. The proposed integration method addresses the issues of stability and larger timesteps. This is achieved by modifying the Semi-Lagrangian method to reduce dissipation and increase accuracy, using improved interpolation and an error correction method. The proposed method allows the rendering of related phenomena like a fireball, dust and smoke clouds, and the simulation of solid interaction - like rigid fracture and rigid body simulation. Our method is flexible enough to afford substantial artistic control over the behavior of the explosion.

关键词： Explosions Solid modeling Fires Computational modeling computer simulation image coding Atmospheric modeling Interpolation Clouds Combustion

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Document image Segmentation as a Spectral Partitioning Problem

Document Image Segmentation as a Spectral Partitioning Probl...

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indian conference on computer vision, graphics & image processing (ICVGIP)

作者： Praveen Dasigi Raman Jain C.V. Jawahar Center for Visual Information Technology IIIT-Hyderabad Hyderabad India

State of art document segmentation algorithms employ ad hoc solutions which use some document properties and iteratively segment the document image. These solutions need to be adapted frequently and sometimes fail to perform well for complex scripts. This calls for a generalized solution that achieves a one shot segmentation that is globally optimal. This paper describes one such solution-based on the optimization problem of spectral partitioning which makes the decision of proper segmentation based on the spectral properties of the pairwise similarity matrix. The solution described in the paper is shown to be general, global and closed form. The claims have been demonstrated on 142 page images from a Telugu book, in a script set in both poetry and prose layouts. This particular class of scripts has been proved to be challenging for the existing state of the art algorithms, where the proposed solution achieves significant results.

关键词： image segmentation Partitioning algorithms Nearest neighbor searches Iterative algorithms Art Optical character recognition software Algorithm design and analysis Natural languages computer vision computer graphics

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Combining Skin-Color Detector and Evidence Aggregated Random Field Models towards Validating Face Detection Results

Combining Skin-Color Detector and Evidence Aggregated Random...

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indian conference on computer vision, graphics & image processing (ICVGIP)

作者： Sreekar Krishna Sethuraman Panchanathan Center for Cognitive Ubiquitous Computing (CUbiC) School of Computing and Informatics (SCI) Arizona State University Tempe AZ USA

In this paper, a framework for validating any generic face detection algorithm's result is proposed. A two stage cascaded face validation filter is described that relies on a skin-color detector and on a face silhouette structure modeler towards increasing face detection capacity of any face detection algorithm. While the skin-color detector combines a static skin-color and a dynamic background-color modeler, the face silhouette structure modeler incorporates an aggregate of random field models combined through a Dempster-Shafer framework of evidence merging. Together, the two modelers validate any face subimage generated by face detection algorithms. Experiments conducted on FERET and on an in-house face database supports the claim for improved face detection results using the proposed filter. An extension of the same framework towards head pose estimation is also suggested.

关键词： Face detection Detectors Skin computer vision Filters Aggregates Humans Computational complexity computer graphics image processing

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Adaptation and Learning for image Based Navigation

Adaptation and Learning for Image Based Navigation

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indian conference on computer vision, graphics & image processing (ICVGIP)

作者： Supreeth Achar C.V. Jawahar Center for Visual Information Technology International Institute of Information Technology Hyderabad India

image based methods are a new approach for solving problems in mobile robotics. Instead of building a metric (3D) model of the environment, these methods work directly in the sensor (image) space. The environment is represented as a topological graph in which each node contains an image taken at some pose in the workspace, and edges connect poses between which a simple path exists. This type of representation is highly scalable and is also well suited to handle the data association problems that effect metric model based methods. In this paper, we present an efficient, adaptive method for qualitative localization using content based image retrieval techniques. In addition, we demonstrate an algorithm which can convert this topological graph into a metric model of the environment by incorporating information about loop closures.

关键词： Navigation Robot sensing systems Mobile robots image retrieval Robot vision systems Robotics and automation image reconstruction Simultaneous localization and mapping Vocabulary computer vision

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