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检索条件"任意字段=15th Indian Conference on Computer Vision Graphics and Image Processing"

共 1004 条记录，以下是141-150 订阅

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Non-rigid Registration using Spectral Graph Wavelet Features 11

Non-rigid Registration using Spectral Graph Wavelet Features

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11th indian conference on computer vision, graphics and image processing (ICVGIP)

作者： thottupattu, Alphin J. Yadav, Shivin Sharma, Avinash Int Inst Informat Technol Hyderabad India

ISBN: (纸本)9781450366151

image registration is an essential step in many computer vision applications which demands high accuracy for significantly random and complex deformations. In medical image processing applications image registration is a basic preprocessing step to non-rigidly align images from different acquisition environments to an atlas image. We propose a novel non-rigid image registration method to get more reliable registration even under noisy conditions with manageable time complexity. the proposed method explores the the inherent multi-resolution capability of wavelets to perform nonrigid registration in a graph environment. the inherent time complexity of wavelet feature map calculation is avoided using Chebyshev Polynomial approximations for the wavelet operators.

关键词： image registration

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Automated Conversion of 2D to 3D image using Manifold Learning 5

Automated Conversion of 2D to 3D Image using Manifold Learni...

引用

5th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Chahal, Nidhi Pippal, Meghna Chaudhury, Santanu Indian Inst Technol Dept Elect Engn Delhi 110016 India

ISBN: (纸本)9781467385640

Automatic technique of 2D to 3D image conversion is proposed using manifold learning and sequential labeling which generates very reliable and accurate 3D depth maps that are very close to ground truth depths. In paper, LLE which is a non linear and neighborhood preserving embedding algorithm is used for depth estimation of a 2D image. And then, fixed point supervised learning algorithm is applied to construct consistent and smooth 3D output. the high dimensional data points or pixels of the input frames can be represented by a linear combination of its nearest neighbors and a lower dimensional point is reconstructed while preserving the local and geometric properties of the frames. the neighbors are assigned to each input point in the image data set and their weight vectors are computed that best linearly reconstruct the input point from its neighbors. To get the depth value of input point in new image, the reconstruction weights of its closest neighbors in training samples are multiplied with their corresponding ground truth depth values. the fixed point learning algorithm takes depths from manifold and other image features as input vectors and generates more consistent and accurate depth images for better 3D conversion.

关键词： Learning algorithms

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Information set based approach for salient object detection 5

Information set based approach for salient object detection

引用

5th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Kapoor, Aditi Biswas, K. K. Hanmandlu, M. Indian Inst Technol Delhi Amar Nath & Shashi Khosla Sch Informat Technol New Delhi 110016 India Indian Inst Technol Delhi Dept Comp Sci & Engn New Delhi 110016 India Indian Inst Technol Delhi Dept Elect Engn New Delhi 110016 India

ISBN: (纸本)9781467385640

Human attention tends to get focused on the most prominent components of a scene which are in sharp contrast with the background. these are termed as salient regions. Saliency is defined in terms of local and global feature contrasts. the human brain perceives an object of salient type based on its difference with the surroundings in terms of color and texture. there have been many color based approaches in the past for salient object detection. In this paper, we define the uncertainty of a window being salient or background in terms of information extracted from different color components. the uncertainty associated with the elements of a fuzzy set is described by a membership function, which gives the degree of association of each element to the set. the overall uncertainty is sought to be quantified by an entropy function. To locate the salient parts of the image, we make use of the entropy to compute a new set of features from color and luminance components of the image. Extensive comparisons with the state-of-the-art methods in terms of precision, recall and F-Measure are made on a publicly available dataset to prove the effectiveness of this approach.

关键词： Membership functions

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image Defencing via Signal Demixing 16

Image Defencing via Signal Demixing

引用

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

作者： Kumar, Veepin Mukherjee, Jayanta Das Mandal, Shyamal Kumar Indian Inst Technol Ctr Educ Technol Kharagpur 721302 W Bengal India Indian Inst Technol Dept Comp Sci & Engn Kharagpur 721302 W Bengal India

ISBN: (纸本)9781450347532

We present a novel algorithm to remove near regular, fence or wire like foreground patterns from an image. the fence detection or fence removal algorithms, developed so far, have poor performance in detecting the fence. We use signal demixing to utilize the sparsity and regularity property of fences to detect them. Results demonstrate the effectiveness of our technique as compared to other state of the art techniques.

关键词： Object detection fence removal image inpainting signal demixing

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Face features-based personality assessment 15

Face features-based personality assessment

引用

International conference on computer graphics, Visualization, computer vision and image processing 2021, CGVCVIP 2021, Connected Smart Cities 2021, CSC 2021 and Big Data Analytics, Data Mining and Computational Intelligence 2021, BIGDACI 2021 - Held at the 15th Multi-conference on computer Science and Information Systems, MCCSIS 2021

作者： Singh, Krishna Kumar Chiranjeevi, Sadu Sivalal, Kethavath Dept. of Computer Science and Engineering RGUKT Nuzvid Nuzvid521 202 India Dept. of Electronics and Communication Engineering RGUKT Nuzvid Nuzvid521 202 India

ISBN: (纸本)9789898704320

Personality assessment has been widely used in the professional psychology and signal processing fields. Recently, it has been a great interest from the computer vision research community in assessing personality from visual data. Many state-of-the-art models are assigned the Big-Five personality indicators using either external judges or personal interviews. We propose Face Features-based Personality Assessment (FFPA) that assesses the personality of a person based on one's facial features. It maps facial appearance into the Big-Five personality indicators, namely Extraversion, Agreeableness Conscientiousness, Neuroticism and Openness. the geometry-based and appearance-based approaches are used to extract features from the face and mapped to the personality indicators using Partial Least Square Regression (PLSR). the corresponding personality indicator values are collected by filling the online form of the Big-Five personality assessor. the computational experiments are performed on a synthetic dataset, consisting of the face images of 200 students. the experimental results show that the proposed model predicts the personality indicators with 0.95 coefficient of determination (approx.) and Mean Squared Error (MSE) is 0.001 (approx.). © 2021 International conference on computer graphics, Visualization, computer vision and image processing 2021, CGVCVIP 2021, Connected Smart Cities 2021, CSC 2021 and Big Data Analytics, Data Mining and Computational Intelligence 2021, BIGDACI 2021 - Held at the 15th Multi-conference on computer Science and Information Systems, MCCSIS 2021. All rights reserved.

关键词： Mean square error

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A Hierarchical Class-Grouping Approach, and a Study of Classification Strategies for Leaf Classification 5

A Hierarchical Class-Grouping Approach, and a Study of Class...

引用

5th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Prajapati, Ravinder Bhavsar, Arnav Sao, Anil Indian Inst Technol Sch Comp & Elect Engn Mandi India

ISBN: (纸本)9781467385640

Fine-grained visual classification has been considered for image data in various domains of environmental importance such as birds, animals and plants. this work considers the classification problem of the latter, based on the leaf shape. Traditional works in such areas typically propose better features, or sophisticated classification frameworks. In this work, we ask a different question: Given simple and efficient features, and a well-known binary classifier such as support vector machine (SVM), among various strategies, what may be a good way to pose the multi-class classification problem as multiple binary classifications ? In this respect, we compare three different strategies, all of which use the same set of features. From our results, we conclude that, one of these three approaches, based on hierarchical class-grouping, clearly outperforms the others, with high classification accuracy. this suggest that classification strategy is an important aspect for the given features and classifiers. To our knowledge, such a study in the fine-grained classification area (and particularly for the nascent area of leafclassification), has not yet been explored.

关键词： Classification (of information)

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Feature Extraction and Identification of indian Currency Notes 5

Feature Extraction and Identification of Indian Currency Not...

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5th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Kamal, Snigdha Chawla, Simarpreet Singh Goel, Nidhi Raman, Balasubramanian Delhi Technol Univ Dept Elect & Commun Engn New Delhi India Indian Inst Technol Dept Comp Sci & Engn Roorkee Uttar Pradesh India

ISBN: (纸本)9781467385640

Banknote identification systems, with their wide applications in Automated Teller Machines (ATMs), vending machines and currency recognition aids for the visually impaired, are one of the most widely researched fields today. the present paper proposes a novel technique for recognition of indian currency banknotes by adopting a modular approach. the proposed work extracts distinct and unique features of indian currency notes such as central numeral, RBI seal, colour band and identification mark for the visually impaired and employs algorithms optimized for the detection of each specific feature. the proposed technique has been evaluated over a large data set for recognition of indian banknotes of various denominations and physical conditions including new notes, wrinkled notes and non-uniform illumination. thorough analysis yields a high true positive rate (desired feature identified correctly) of 95.11% and a low false positive rate (undesired feature recognition minimized) of 0.09765% for emblem recognition, an accuracy of 97.02% for central numeral detection, and 100% accuracies for both recognition of identification mark and colour matching in CIE LAB colour space.

关键词： Feature extraction

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Gaussian Mixture Model for Summarization of Surveillance Videos 5

Gaussian Mixture Model for Summarization of Surveillance Vid...

引用

5th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Sujatha, C. Mudenagudi, Uma BVB Coll Engn & Tech Dept CSE Hubli 580031 India BVB Coll Engn & Tech Deparment ECE Hubli 580031 India

ISBN: (纸本)9781467385640

We propose a method to address the problem of Video Summarization, which aims to generate a summarized video by preserving the salient activities of the input video for a user specified time. We model the motion of a feature points as Gaussian Mixture Model (GMM) to select the key feature points, which in-turn estimate the salient frames. the saliency of feature points depends on the contribution of motion in entire video and user specified time duration of summary. We generate a summarized video keeping chronology of salient frames to avoid the viewing ambiguity for the viewers. We demonstrate the proposed method for different stored surveillance videos and achieve retention ratio as 1 for the closest condensation ratio obtained for stroboscopic approach and also demonstrate the proposed GMM method with interactively selected region of interest (ROI) based results.

关键词： Motion of feature point Optical flow GMM Chronology of activities ROI

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A Framework For Dynamic Hand Gesture Recognition Using Key Frames Extraction 5

A Framework For Dynamic Hand Gesture Recognition Using Key F...

引用

5th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Pathak, Bhumika Jalal, Anand Singh Agrawal, Subhash Chand Bhatnagar, Charul GLA Univ Mathura India

ISBN: (纸本)9781467385640

Hand Gesture Recognition is one of the natural ways of human computer interaction (HCI) which has wide range of technological as well as social applications. A dynamic hand gesture can be characterized by its shape, position and movement. this paper presents a user independent framework for dynamic hand gesture recognition in which a novel algorithm for extraction of key frames is proposed. this algorithm is based on the change in hand shape and position, to find out the most important and distinguishing frames from the video of the hand gesture, using certain parameters and dynamic threshold. For classification, Multiclass Support Vector Machine (MSVM) is used. Experiments using the videos of hand gestures of indian Sign Language show the effectiveness of the proposed system for various dynamic hand gestures. the use of key frame extraction algorithm speeds up the system by selecting essential frames and therefore eliminating extra computation on redundant frames.

关键词： Hand gesture recognition key frame extraction sign language recognition muliclass support vector machine skin color segmentation

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Color Harmonization for Videos

Color Harmonization for Videos

引用

6th indian conference on computer vision, graphics and image processing

作者： Sawant, Nikhil Mitra, Niloy J. Indian Inst Technol Dept CSE Delhi India

ISBN: (纸本)9781424442195

Color harmonization is an artistic technique to adjust the colors of a given image in order to enhance their visual harmony. In this paper we present a method to automatically improve the color harmony of images. Harmonization is performed using a carefully designed optimization in the hue space, while keeping the saturation and intensity components unchanged. Finally, for videos, we pose the problem as an efficient joint optimization in space and time, thus minimizing flickering or visual artifacts in the harmonized output video. We report the performance of our algorithm on a variety of test images and video sequences.

关键词： Color

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