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Saliency detection based on a sparsity of segments model 14

Saliency detection based on a sparsity of segments model

引用

9th indian conference on computer vision, graphics and image processing, ICVGIP 2014

作者： Hati, Avik Chaudhuri, Subhasis Velmurugan, Rajbabu Dept. of Electrical Engineering Indian Institute of Technology Bombay Mumbai India

ISBN: (纸本)1595930361

In this paper, we propose a region based saliency detection algorithm using a total variation based regularizer. We aim to obtain salient objects that are uniformly highlighted. the use of the regularizer facilitates the removal of textures from the image. this leads to an image that contains piecewise constant gray-valued segments. this texture-free image is sparsely segmented into a small number of regions using the expectation maximization algorithm assuming a Gaussian mixture model. We compute saliency of regions using their intensity and spatial features. the saliency map is then thresholded to obtain the salient regions of the image. Next we employ an image matting technique to extract the exact boundaries of the salient objects from the image. this approach leads to noise-free saliency maps containing uniformly highlighted salient regions. the experimental comparison with existing saliency detection algorithms demon-strates the superiority of the proposed technique. Copyright 2014 ACM.

关键词： image segmentation

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Camouflaging motion blur: Art or science? 14

Camouflaging motion blur: Art or science?

引用

9th indian conference on computer vision, graphics and image processing, ICVGIP 2014

作者： Rao, M. Purnachandra Prabhu, Sahana M. Rajagopalan, A.N. Seetharaman, Guna Department of Electrical Engineering Indian Institute of Technology Madras India Information Directorate AFRL RIEA RomeNY United States

ISBN: (纸本)1595930361

Camouaging an object in a photograph is normally performed with the intent of unnoticeably hiding it within a given image. In this work, we give a different dimension to this problem and raise the interesting issue of camouaging motion blur with special relevance to non-uniformly blurred images. Given a blurred photograph, we apply a suitably derived blurring model to smear a target object and naturally blend it into the motion blurred background by using alpha matting. We validate our photo-realistic compositing approach on several synthetic and real examples. Copyright 2014 ACM.

关键词： Photography

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LR-HyClassify: A Low Rank Based Framework for Classification of Degraded Hyperspectral images 7th

LR-HyClassify: A Low Rank Based Framework for Classification...

引用

7th National conference on computer vision, Pattern Recognition, image processing, and graphics, NCVPRIPG 2019

作者： Sarkar, Sourish Sahay, Rajiv R. Department of Electrical Engineering Indian Institute of Technology Kharagpur India

ISBN: (纸本)9789811586965

We propose a novel framework for the classification of hyperspectral data corrupted by severe degradation. We propose an optimization framework for extracting discriminative features from noisy hyperspectral data which are then passed onto a simple classifier which exploits both the spatial and spectral correlations in the data. Instead of directly extracting the features from the noisy input data, we learn a basis matrix from the underlying clean data using a combination of non-negative matrix factorization and nuclear-norm minimization. the input degraded data are then projected onto the basis vectors to obtain features. We use structural incoherence to maximize the discriminative ability of the features, which, to the best of our knowledge, is being used for the first time in hyperspectral image processing literature. We show the deterioration in the performance of classification algorithms with the progressive addition of noise while demonstrating the robustness of our algorithm. We evaluate the performance of our algorithm on three well known datasets, namely, Botswana, Salinas and indian Pines, obtaining state-of-the-art results that validate the efficacy of our algorithm. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Non-negative matrix factorization

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Haptic rendering of variable density point cloud through local kernel bandwidth estimation 12

Haptic rendering of variable density point cloud through loc...

引用

8th indian conference on computer vision, graphics and image processing, ICVGIP 2012

作者： Sreeni, K.G. Chaudhuri, Subhasis Vision and Image Processing Laboratory Department of Electrical Engineering Indian Institute of Technology Bombay Powai Mumbai 400076 India

ISBN: (纸本)9781450316606

Haptic rendering of a point cloud data without a precomputed mesh structure is always a difficult problem. this paper tries to solve the problem of real time rendering a variable density 3D point cloud data as an optimization problem with a local kernel bandwidth estimation. In order to avoid the ambiguity of deciding the direction of reaction force while rendering the data we prefer a proxy based renderer. To avoid the proxy sinking into the object during collision the proxy point is always kept at minimum distance away from the object surface approximated by the point cloud. this minimum distance is computed during the rendering process depending on the local density of the points in the data using the kernel bandwidth estimation. Once collision is detected, we minimize a cost function depending on the current haptic interaction point (HIP) and proxy positions and find a new goal position for the proxy corresponding to the local minimum of the cost function. We validate the proposed technique by comparing the rendered force with the reaction force computed using a known spherical object. © 2012 ACM.

关键词： Cost functions

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Synthesis of emotional expressions specific to facial structure 12

Synthesis of emotional expressions specific to facial struct...

引用

8th indian conference on computer vision, graphics and image processing, ICVGIP 2012

作者： Agarwal, Swapna Chatterjee, Moitreya Mukherjee, Dipti Prasad Indian Statistical Institute 203 B. T. Road Kolkata 700108 India

ISBN: (纸本)9781450316606

Imposing expressions on expression-neutral human face images is an interesting application of human-computer-interaction, animation, entertainment and other such fields. the objective of this paper is to impose one of the six prototypic emotional expressions i.e., Joy, Surprise, Disgust, Fear, Anger and Sorrow to a given expression-neutral face image. For this, we first establish individual models for each of the six prototypic expressions. this model is independent of the shape and texture i.e., identity of the subjects in the training video sequences. Given an intensity of a particular expression, we find the changes in the shape and texture due to a particular expression from the derived models. these changes are added to the automatically annotated test image on which the expression is to be imposed. the major contributions of the paper are: (1) Developing a method for finding facial structure specific changes of a subject for imposing a particular expression and (2) Establishing a nonlinear relationship between the expression intensity and the corresponding facial changes. the experimental results show that the proposed method is better compared to another related method. the proposal is also good at preserving the identity of the subject while imposing a given expression on the expression-neutral face image. © 2012 ACM.

关键词： Human computer interaction

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Deep neural network for foreground object segmentation: An unsupervised approach 6th

Deep neural network for foreground object segmentation: An u...

引用

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

作者： Majumder, Avishek Venkatesh Babu, R. Indian Institute of Science BangaloreKarnataka560012 India

ISBN: (纸本)9789811300196

Saliency plays a key role in various computer vision tasks. Extracting salient regions from images and videos have been a well established problem of computer vision. While segmenting salient objects from images depend only on static information, temporal information in a video can make non salient objects be salient due to movement. Besides the temporal information, there are other challenges involved with video segmentation, such as 3D parallax, camera shake, motion blur, etc. In this work, we propose a novel unsupervised end to end trainable, fully convolutional deep neural network for object segmentation. Our model is robust and scalable across scenes, as it is tested unsupervisedly and can easily infer which objects constitute the foreground of the image. We run various tests on two well established benchmarks of video object segmentation, DAVIS and FBMS-59 datasets. We report our results and compare them against the state of the art methods. © Springer Nature Singapore Pte Ltd. 2018.

关键词： computer vision

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Application of forgery localization in overlay text detection 14

Application of forgery localization in overlay text detectio...

引用

9th indian conference on computer vision, graphics and image processing, ICVGIP 2014

作者： Hooda, Amit Kathuria, Madhur Pankajakshan, Vinod Department of Electronics and Communication Engineering Indian Institute of Technology Roorkee Roorkee Uttarakhand247 667 India

ISBN: (纸本)1595930361

Detection of text embedded in images and videos is very useful in applications like indexing and retrieval of multimedia content. there exist very few techniques which can differentiate between overlay text which is embedded artificially and scene text which occurs naturally in images. this paper proposes an efficient method for detection and localization of overlay text from still images. By using colour filter array(CFA)-based forgery localization method, the proposed technique successfully removes any scene text present in the image. Experimental results on a database of 315 images demonstrate the efficiency of the proposed method. Copyright 2014 ACM.

关键词： Digital forensics

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Swift Convergence: Federated Learning Enhanced with GMMs for image Classification 1

引用

8th International conference on computer vision and image processing (CVIP)

作者： Palit, Aditi Nandanavanam, Sai Pragna Yeturu, Kalidas Indian Inst Technol Tirupati Dept Comp Sci & Engn Tirupati Andhra Pradesh India

ISBN: (数字)9783031581816

ISBN: (纸本)9783031581809;9783031581816

In Federated learning (FL), FederatedAveraging(FedAvg) is widely used to compute the weighted mean of local models in the parametric space over time on a central server by exchanging intermediate updates over multiple rounds of communication. However, this approach requires many communication rounds for the central model to learn data generalization. Each local model updates the central model parameters in different directions of the multi-dimensional parameter space. To address this challenge, we propose FedGMMinit: Federated Initialization with Gaussian Mixture Model, which adjusts initial central model gradients by pre-training the model on synthetic data generated from a Gaussian Mixture Model (GMM). For each label in the client's dataset, a GMM is built. the pre-trained weights are then communicated to the selected clients to initialize FedAvg. To maintain data privacy, only the client's representation of the Gaussian is passed to the server. Our proposed approach is tested on MNIST digit datasets for image classification. It shows a reduction of 10-15 communication rounds required by the central model to achieve target accuracy for both IID and non-IID distributions. In the scope of the study, we also discovered that clustering clients and training them with global models also contributed to the overall improvement of convergence. We call this clustering method as FedGMMCluster.

关键词： Communication rounds Gaussian mixture model Initialization Proxy dataset Clustering

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vision based human pose estimation for virtual cloth fitting 14

Vision based human pose estimation for virtual cloth fitting

引用

9th indian conference on computer vision, graphics and image processing, ICVGIP 2014

作者： Saha, Sourav Ganguly, Pritha Chaudhury, Subhajit Jadavpur University Kolkata India National Institute of Technology Durgapur India Indian Institute of Technology Bombay India

ISBN: (纸本)1595930361

this paper proposes a real-time solution to setting up a virtual trial-room for on-line portals selling apparels using a generic web camera interface to the portal. the user selects an image of an apparel from the on-line display and captures his/her own videos. the proposed method detects the pose of the user as well as various anthropomorphic features such as length and thickness of upper limbs and the dimensions of the torso. We use a background subtraction based methodology to segment out the human body from the image. the segmented human body contour is represented by a 1D curve by computing the distance of a point on the contour from the body centroid. Various extremities of body parts are found out by measuring the curvature. Using the detected feature points, we use a cloth fitting algorithm to fit the garment to the users body. the entire process is performed at 30fps, providing a realistic rendering of virtual clothing for any user.

关键词： image segmentation

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Low Resource Degraded Quality Document image Binarization - Domain Adaptation is the Way 13

Low Resource Degraded Quality Document Image Binarization - ...

引用

13th indian conference on computer vision, graphics, and image processing, ICVGIP 2022

作者： Kundu, Ahana Bhattacharya, Ujjwal Computer Vision and Pattern Recognition Indian Statistical Institute West Bengal Kolkata India

ISBN: (纸本)9781450398237

Usually, image binarization plays a crucial role in automatic analysis of degraded documents from their captured images. However, this binarization task is often difficult due to a number of reasons including the high similarity between noisy background and faded foreground pixels. the study presented here is particularly focused on binarization of images of low-resource degraded quality documents based on a set of recently collected image samples of several rare, ancient and severely degraded quality printed documents of Bangla, the 2nd and 5th most popular script of India and the world respectively. this new collection of degraded document image samples will henceforth be referred as 'ISIDDI2' and it consists of 139 images of Bangla old document pages. Samples of 'ISIDDI', another existing database of degraded Bangla document image samples, have also been used in the present study. A novel deep architecture based on attention UNET++ with dilated convolution operation is proposed for this binarization task. the model is optimized using human vision perceptible distance reciprocal distortion (DRD) loss. Since the binarization ground truth of samples of both 'ISIDDI2' and 'ISIDDI' are not available, the proposed network has been trained using samples of DIBCO and H-DIBCO datasets and an unsupervised domain adaptation (DA) module is employed for adaptation of the proposed architecture to the degradation patterns of 'ISIDDI2' or 'ISIDDI' samples. the proposed binarization strategy includes certain post-processing operation based on a modified k-neighbourhood based approach for recovery of broken characters. Results of our extensive experimentation show that the proposed binarization strategy has improved the binarization output of state-of-the-art methods on both ISIDDI2 and ISIDDI datasets. Also, its performance on well-known DIBCO samples is satisfactory. © 2022 ACM.

关键词： Network architecture

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