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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 1495 条记录，以下是1051-1060 订阅

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Single View Homography Estimation for an Inclined Textured Planar Surface: Overcoming the Inverse and Ill-Posed Challenge! 23

Single View Homography Estimation for an Inclined Textured P...

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proceedings of the fourteenth indian conference on computer vision, graphics and image processing

作者： Pooja Kumari Sukhendu Das IIT Madras IN Indian Institute of Technology Madras IN

ISBN: (纸本)9798400716256

Homography estimation is a crucial step in many computer vision problems involving the planar transformation of an image from one view to another. Generally, from two image views of a scene with a planar patch, one can compute the homography matrix (H) using Direct Linear Transformation (DLT) or its variants. In this study, we work on the inverse scenario to solve an ill-posed problem, where given only a single image (Math 1) of an inclined textured planar surface, we attempt to estimate both H and the orthogonal view (Math 2) of the planar surface. We propose to solve this problem of homography Estimation using an optimization framework. To the best of our knowledge, there has barely been any work done on this inverse scenario of homography estimation from only a single image view. The research presented in this paper successfully achieves image rectification and homography computation by assuming a perspective transformation on an upright planar patch when viewed by a camera placed exactly in front of it. A cost function with suitable constraints is utilized to refine homography estimation. Experimental results reveal the efficiency of the proposed approach in the case of images of checkerboard and other textured planar surfaces (real-world images with lines and other prominent textures).

关键词： DLT Homography LM image perspective optimization texture

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Word-Wise Handwriting Based Gender Identification Using Multi-Gabor Response Fusion 4th

Word-Wise Handwriting Based Gender Identification Using Mult...

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4th Workshop on Document Analysis and Recognition, DAR 2018, held in Conjunction with the 11th indian conference on vision, graphics, and image processing, ICVGIP 2018

作者： Asadzadeh Kaljahi, Maryam Vidya Varshini, P.V. Shivakumara, Palaiahnakote Pal, Umapada Lu, Tong Guru, D.S. Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur Malaysia Vellore Institute of Technology VelloreTamil Nadu India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India National Key Lab for Novel Software Technology Nanjing University Nanjing China Department of Studies in Computer Science Manasagangotri University of Mysuru Mysore India

ISBN: (纸本)9789811393600

Handwriting based gender identification at the word level is challenging due to free style writing, use of different scripts, and inadequate information. This paper presents a new method based on Multi-Gabor Response (MGR) fusion for gender identification at the word level. It first explores weighted-gradient features for word segmentation from text line images. For each word, the proposed method obtains eight Gabor response images. Then it performs sliding window operation over MGR images to smooth the values. For each smoothed MGR images, we perform fusion operation that chooses the Gabor response value which contributes to the highest peak in the histogram. This process results in a feature matrix, which is fed to CNN for gender identification. Experimental results on our dataset (multi scripts) apart from English, and benchmark databases, namely, IAM, KHATT, and QUWI, which contain handwritten English and Arabic text, show that the proposed method outperforms the existing methods. © Springer Nature Singapore Pte Ltd. 2019.

关键词： image segmentation

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Flow-free video object segmentation 6th

Flow-free video object segmentation

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6th National conference on computer vision, Pattern Recognition, image processing and graphics, NCVPRIPG 2017

作者： Vora, Aditya Raman, Shanmuganathan Electrical Engineering Indian Institute of Technology Gandhinagar GandhinagarGujarat382355 India

ISBN: (纸本)9789811300196

Segmenting foreground object from a video is a challenging task because of large deformations of objects, occlusions, and background clutter. In this paper, we propose a frame-by-frame but computationally efficient approach for video object segmentation by clustering visually similar generic object segments throughout the video. Our algorithm segments object instances appearing in the video and then performs clustering in order to group visually similar segments into one cluster. Since the object that needs to be segmented appears in most part of the video, we can retrieve the foreground segments from the cluster having maximum number of segments. We then apply a track and fill approach in order to localize the object in the frames where the object segmentation framework fails to segment any object. Our algorithm performs comparably to the recent automatic methods for video object segmentation when benchmarked on DAVIS dataset while being computationally much faster. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Motion compensation

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Disparity based depth estimation using light field camera 21

Disparity based depth estimation using light field camera

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12th indian conference on computer vision, graphics and image processing, ICVGIP 2021

作者： Nehra, Suresh Das, Tamal Chakraborty, Simantini Biswas, P.K. Mukhopadhyay, J. Indian Institute of Technology Kharagpur India National Institute of Technology Agartala India

ISBN: (纸本)9781450391276

Light field cameras have a unique feature of capturing the direction of light rays along with its intensity. This additional information is used to estimate the depth of a 3-D scene. Recently a considerable amount of research has been done in depth estimation using light field data. However, these depth estimation methods heavily rely on iterative optimization techniques and do not fully exploit the inherent structured light field data. In this paper, we present a novel three-step disparity based algorithm to estimate accurate depth maps of a light field image. First, an initial depth map of scene points is estimated using principal views by estimating the disparity of segments in the central image. This initial depth helps in resolving ambiguity in depth propagation of refined depth map in Epi-Polar line images (EPIs). Second, refined depth is estimated at lines using the disparity vector in EPIs. Finally, refined depth at lines in EPIs is propagated to other locations using the initial depth map. We also provided a synthetic data-set having inherent characteristic of a light field. We have tested our approach on a variety of real-world scenes captured with Lytro Illum camera and also on synthetic images. The proposed method outperforms several state-of-the-art algorithms. © 2021 ACM.

关键词： Cameras

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Knowledge Distillation with Ensemble Calibration 23

Knowledge Distillation with Ensemble Calibration

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proceedings of the fourteenth indian conference on computer vision, graphics and image processing

作者： Ishan Mishra Riyanshu Jain Dhruv Viradiya Divyam Patel Deepak Mishra Computer Science and Engineering Indian Institute of Technology Jodhpur India Computer Science and Engineering Indian Institute of Technology Jodhpur India Electrical Engineering Indian Institute of Technology Jodhpur India

ISBN: (纸本)9798400716256

Knowledge Distillation is a transfer learning and compression technique that aims to transfer hidden knowledge from a teacher model to a student model. However, this transfer often leads to poor calibration in the student model. This can be problematic for high-risk applications that require well-calibrated models to capture prediction uncertainty. To address this issue, we propose a simple and novel technique that enhances the calibration of the student network by using an ensemble of well-calibrated teacher models. We train multiple teacher models using various data-augmentation techniques such as cutout, mixup, CutMix, and AugMix and use their ensemble for knowledge distillation. We evaluate our approach on different teacher-student combinations using CIFAR-10 and CIFAR-100 datasets. Our results demonstrate that our technique improves calibration metrics (such as expected calibration and overconfidence errors) while also increasing the accuracy of the student network.

关键词： Augmentation Confidence Calibration Ensemble Knowledge Distillation

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InMDb: indian Movie Database for Emotion Analysis 23

InMDb: Indian Movie Database for Emotion Analysis

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proceedings of the fourteenth indian conference on computer vision, graphics and image processing

作者： Ritik Garg Rushil Thareja Manak Bisht Manavjeet Singh Sarthak Arora Jainendra Shukla IIIT Delhi IN IIIT-Delhi IN

ISBN: (纸本)9798400716256

Cinematic experiences, characterized by intricate audio-visual stimuli, foster profound emotional engagement. However, the correlation between audience emotions, physiological responses, film genres, and ratings, particularly in the underexplored Bollywood context, remains largely uncharted. Understanding this intricate interplay can provide filmmakers valuable insights for content adaptation. Addressing this research gap, we introduce "InMDB: indian Movie DataBase," a comprehensive multimodal dataset that examines emotional responses elicited by Bollywood trailers, using both self-reported measures and physiological data. Our meticulous statistical analysis of the dataset deepens the understanding of how emotions and their subsequent physiological responses correlate with, and potentially influence, film ratings and categories, offering novel insights into emotional engagement in the cinematic context.

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Brain MR image segmentation using tabu search and hidden markov random field model

Brain MR image segmentation using tabu search and hidden mar...

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2nd indian International conference on Artificial Intelligence, IICAI 2005

作者： Nanda, P.K. Patra, D. Pradhan, A. Department of Electrical Engineering Image Processing and Computer Vision Laboratory National Institute of Technology Rourkela Orissa 769008 India

ISBN: (纸本)0972741216

In this paper, we propose a hybrid Tabu Expectation Maximization (TEM) Algorithm for segmentation of Brain Magnetic Resonance (MR) images in both supervised and unsupervised framewrok. Gaussian Hidden Markov Random Field (GHMRF) is used to model the available degraded image. In supervised framework, the apriori image MRF model parameters as well as the GHMRF model parameters are assumed to be known. The class labels are estimated using the Maximum a Posteriori (MAP) estimation criterion. In unsupervised framework, the problem of model parameter estimation and label estimation is formulated in Expectation Maximization (EM) framework. The labels are estimated using the proposed Tabu Search algorithm while the model parameters are the maximum likelihood estimates. Our proposed algorithm yields results with arbitrary initial paramater set and thus overcomes the problem of proper choice of initial parameters. The results obtained are comparable with the results obtained by using the algorithm proposed by Zhang ***. [15] , where the Iterated Conditional Mode (ICJM) algorithm is used for computing the MAP estimates. Copyright © IICAI 2005.

关键词： Tabu search

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A novel framework for multi-focus image fusion

A novel framework for multi-focus image fusion

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National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Gaurav Bhatnagar Q.M. Jonathan Wu Indian Institute of Technology Jodhpur Jodhpur Rajasthan India University of Windsor Windsor ON Canada

One of the foremost requisite for human perception and computer vision task is to get an image with all objects in focus. The image fusion process, as one of the solutions, allows getting a clear fused image from several images acquired with different focus levels of a scene. In this paper, a novel framework for multi-focus image fusion is proposed, which is computationally simple since it realizes only in the spatial domain. The proposed framework is based on the fractal dimensions of the images into the fusion process. The extensive experiments on different multi-focus image sets demonstrate that it is consistently superior to the conventional image fusion methods in terms of visual and quantitative evaluations.

关键词： image fusion Fractals Measurement Wavelet transforms Principal component analysis image quality

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image deblurring in super-resolution framework

Image deblurring in super-resolution framework

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National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Srimanta Mandal Anil Kumar Sao School of Computing and Electrical Engineering Indian Institute of Technology Mandi India

In all image processing applications, it is important to extract the appropriate information from an image. But often the captured image is not clear enough to give the required information due to the imaging environment. Thus, it is essential to enhance the clarity of the image by some post-processing techniques. image deblurring is one of such techniques to remove the blurry effect of the captured image. This paper looks into this problem in a different way, where the deblurring of an image is addressed by solving image super-resolution problem. The blurred image is first down-sampled and then it is fed to the super-resolution framework to produce the deblurred high resolution image. In addition, the proposed approach states the requirement of edge preservation in the problem. The experimental results are comparable with the existing image deblurring algorithms.

关键词： PSNR image resolution image edge detection Boats Data mining Deconvolution Interpolation

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Real-Time Rendering and Manipulation of Large Terrains

Real-Time Rendering and Manipulation of Large Terrains

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

作者： Shiben Bhattacharjee Suryakant Patidar P.J. Narayanan Center for Visual Information Technology International Institute of Information Technology Hyderabad India

Terrains are challenging geometric objects for real-time rendering and interactive manipulation. State-of-the-art terrain rendering systems use custom, multi-resolution, representations like geometry clipmaps for fast rendering on the GPU. In this paper, we present a system that exploits the power and flexibility of the modern GPUs to store, render, and manipulate terrains with minimal CPU involvement. The central idea is to use a regular-grid representation and fixed size blocks/tiles that change in resolution. The potentially visible portion of the terrain is cached at the highest necessary resolution and is rendered from the GPU. The CPU sends a light geometry template which is expanded by the Geometry Shader to the triangles, using the heights stored in the GPU Cache. The CPU performs a coarse culling of the tiles with the GPU performing fine culling. The GPU cache is updated continuously as the viewpoint changes. Our system enables the terrain to be modified procedurally or edited interactively on the GPU with no CPU involvement. The terrain can also interact with a large number of external objects in real-time entirely within the GPU. We achieve a consistent rendering rate of 100 frames per second with terrain modification and interactions as well as a triangle rate of upto 350 million per second on an Nvidia 8800 GTX GPU for large terrains, with a CPU load below 10%.

关键词： Geometry Rendering (computer graphics) Tiles Information technology Physics computer vision computer graphics image processing Aerospace simulation Geographic Information Systems

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