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

12th Indian Conference on Computer Vision, Graphics, and Ima...

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

ISBN: (纸本)9789811941351

the proceedings contain 17 papers. the special focus in this conference is on computer vision, graphics, and image processing. the topics include: the Ikshana Hypothesis of Human Scene Understanding;worst-Case Adversarial Perturbation and Effect of Feature Normalization on Max-Margin Multi-label Classifiers;Catch Me if You Can: A Novel Task for Detection of Covert Geo-Locations (CGL);MATIC: Memory-Guided Adaptive Transformer for image Captioning;Semantic Map Injected GAN Training for image-to-image Translation;textGen3D: A Real-Time 3D-Mesh Generation with Intersecting Contours for Text;comparative Analysis of Neural Architecture Search Methods for Classification of Cultural Heritage Sites;heritage Representation of Kashi Vishweshwar Temple at Kalabgoor, Telangana with Augmented Reality Application Using Photogrammetry;augmented Data as an Auxiliary Plug-In Toward Categorization of Crowdsourced Heritage Data;evolution of Bagbazar Street through Visibility Graph Analysis (1746–2020);mapping Archaeological Remains of 14th Century Fort of Jahanpanah Using Geospatial Analysis;spatial Analysis and 3d Mapping Historic Landscapes—Implications of Adopting an Integrated Approach in Simulation and Visualization of Landscapes;HSADML: Hyper-Sphere Angular Deep Metric Based Learning for Brain Tumor Classification;model Compression Based Lightweight Online Signature Verification Framework.

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Proceedings of icvgip 2021 - 12th indian conference on computer vision, graphics and image processing

Proceedings of ICVGIP 2021 - 12th Indian Conference on Compu...

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

ISBN: (纸本)9781450391276

the proceedings contain 49 papers. the topics discussed include: teaching GANs to sketch in vector format;iterative gradient encoding network using feature co-occurrence loss for single image reflection removal;MSDNet: a novel multi-stage progressive image dehazing network;monocular multi-layer layout estimation for warehouse racks;cross-view kernel similarity metric learning using pairwise constraints for person re-identification;abnormality detection and classification of macular diseases from optical coherence tomography images: using feature space comparison;a novel unsupervised thresholding technique for Landsat image change detection;robust brain state decoding using bidirectional long short term memory networks in functional MRI;NTU-X: an enhanced large-scale dataset for improving pose-based recognition of subtle human actions;and interpretive self-supervised pre-training: boosting performance on visual medical data.

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Learning Feature Trajectories Using Gabor Filter Bank for Human Activity Segmentation and Recognition

Learning Feature Trajectories Using Gabor Filter Bank for Hu...

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

作者： Gupta, Sunil Kumar Kumar, Y. Senthil Ramakrishnan, K. R. Indian Inst Sci Bangalore 12 Karnataka India

ISBN: (纸本)9781424442195

We describe a novel method for human activity segmentation and interpretation in surveillance applications based on Gabor filter-bank features. A complex human activity is modeled as a sequence of elementary human actions like walking, running, jogging, boxing, hand-waving etc. Since human silhouette can be modeled by a set of rectangles, the elementary human actions can be modeled as a sequence of a set of rectangles with different orientations and scales. the activity segmentation is based on Gabor filter-bank features and normalized spectral clustering. the feature trajectories of an action category are learnt from training example videos using Dynamic Time Warping. the combined segmentation and the recognition processes are very efficient as both the algorithms share the same framework and Gabor features computed for the former can be used for the later We have also proposed a simple shadow detection technique to extract good silhouette which is necessary for good accuracy of an action recognition technique.

关键词： Gabor filters

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Proceedings of the Satellite Workshops of icvgip 2021 1

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丛书名： Lecture Notes in Electrical Engineering

1000年

作者： Uma Mudenagudi Aditya Nigam Ravi Kiran Sarvadevabhatla Ayesha Choudhary

ISBN: (数字)9789811941368

ISBN: (纸本)9789811941351;9789811941382

this book constitutes peer-reviewed proceedings of satellite workshops of the 12th indian conference on computer vision, graphics, and image processing (icvgip 2021). the book focuses on medical image processing, digital heritage, document analysis and recognition, and computer vision applications. the first part includes submissions on digital archiving and restoration methods with interesting and innovative research components. the second part focuses on medical imaging modalities including MRI, X-ray, CT, imaging in nuclear medicine, medical ultrasound, optical and confocal microscopy, and video and range data images. the third part deals with document analysis and recognition and focuses on text recognition, document layout analysis, understanding, historical and degraded document analysis, datasets, performance evaluation, metrics, etc. the fourth part of this book includes research work from academia and industry across the globe on smart, innovative, and practical applications of computer vision for industrial and societal impact. this book shares innovative ideas, experience and expertise, and ongoing research ideas and will be helpful for researchers and practitioners in academia and industry.

关键词： Signal, image and Speech processing computer Imaging, vision, Pattern Recognition and graphics Data Structures and Information theory Artificial Intelligence

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Towards interpretable facial emotion recognition 21

Towards interpretable facial emotion recognition

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

作者： Malik, Sarthak Kumar, Puneet Raman, Balasubramanian Indian Institute of Technology Roorkee India

ISBN: (纸本)9781450391276

In this paper, an interpretable deep-learning-based system has been proposed for facial emotion recognition. A novel approach to interpret the proposed system's results, Divide & Conquer based Shapley additive explanations (DnCShap), has also been developed. the proposed approach computes 'Shapley values' that denote the contribution of each image feature towards a particular prediction. the Divide and Conquer algorithm has been incorporated for computing the Shapley values in linear time instead of the exponential time taken by the existing interpretability approaches. the experiments performed on four facial emotion recognition datasets, i.e., FER-13, FERG, JAFFE, and CK+, resulted in the emotion classification accuracy of 62.62%, 99.68%, 91.97%, and 99.67%, respectively. the results show that DnCShap has consistently interpreted the highly relevant facial features for the emotion classification for various datasets. © 2021 ACM.

关键词： Emotion Recognition

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Abnormality detection and classification of macular diseases from optical coherence tomography images: Using feature space comparison 21

Abnormality detection and classification of macular diseases...

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

作者： Ashok, L.R. Sreeni, K.G. Computer Vision Lab Dept.Electronics and Communication College of Engineering Kerala Trivandrum India

ISBN: (纸本)9781450391276

Optical Coherence Tomography (OCT) is a non-invasive imaging technology for diagnosing various macular pathologies. It assists ophthalmologists to detect abnormalities in the retina and thereby avoid many sight-threatening conditions. However, manual detection process depends on the experience of the clinical practitioner and it is a time-consuming process. Automatic detection of abnormalities using computer algorithms allows the clinical practitioner to detect the abnormalities in a faster and accurate manner. Here, a Deep learning-based approach is proposed which can detect abnormal retinal images in various disease classes which are not limited to classes present in the training data-set. the performance of the Abnormality detector is tested on UCSD, Kaggle & OCTID data-sets and obtained an accuracy of 99.80%, 99.90% & 94.59%, respectively. the performance of Classifier is also tested on UCSD & Kaggle data-sets and obtained an accuracy of 97.7%, 99.79%, respectively. © 2021 ACM.

关键词： Optical tomography

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Deep fusion of visual signatures for client-server facial analysis 16

Deep fusion of visual signatures for client-server facial an...

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

作者： Bhattarai, Binod Sharma, Gaurav Jurie, Frederic Normandie Univ UNICAEN ENSICAEN CNRSGREYC Caen France IIT Kanpur Comp Sci & Engn Kanpur Uttar Pradesh India

ISBN: (纸本)9781450347532

Facial analysis is a key technology for enabling humanmachine interaction. In this context, we present a client-server framework, where a client transmits the signature of a face to be analyzed to the server, and, in return, the server sends back various information describing the face e.g. is the person male or female, is she/he bald, does he have a mustache, etc. We assume that a client can compute one (or a combination) of visual features;from very simple and efficient features, like Local Binary Patterns, to more complex and computationally heavy, like Fisher Vectors and CNN based, depending on the computing resources available. the challenge addressed in this paper is to design a common universal representation such that a single merged signature is transmitted to the server, whatever be the type and number of features computed by the client, ensuring nonetheless an optimal performance. Our solution is based on learning of a common optimal subspace for aligning the different face features and merging them into a universal signature. We have validated the proposed method on the challenging CelebA dataset, on which our method outperforms existing state-of-art methods when rich representation is available at test time, while giving competitive performance when only simple signatures (like LBP) are available at test time due to resource constraints on the client.

关键词： Local binary pattern

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MSDNet: A novel multi-stage progressive image dehazing network 21

MSDNet: A novel multi-stage progressive image dehazing netwo...

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

作者： Manu, Chippy M. Sreeni, K.G. Computer Vision Lab Dept. Electronics and Communication College of Engineering Kerala Trivandrum India

ISBN: (纸本)9781450391276

this paper presents a novel algorithm to dehaze a given hazy input image using a Multi-Stage progressive image Dehazing Network (MSDNet) architecture. the proposed multi-stage strategy framework splits the challenge of image recovery into sub-tasks for a degraded image to be gradually restored. the network is trained with images from two benchmark datasets - RESIDE and NTIRE 2021. Experimental evaluations have been conducted with several hazy images from different datasets. the performance evaluation of MSDNet is done using various metrics such as Peak-Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measurement (SSIM), Feature Similarity Metric (FSIM), Visibility Index (VI), Realness Index (RI), Fog Aware Density Evaluator (FADE), Naturalness image Quality Evaluator (NIQE) and Blind/Referenceless image Spatial Quality Evaluator (BRISQUE). An average PSNR of 27.687, 36.25, 34.98, 20.52, and 20.97 have been obtained with images from ITS, SOTS indoor, SOTS outdoor, Dense-Haze, and NH-Haze datasets, respectively. the experimental results reveals the enhanced performance of MSDNet compared to other state-of-the-art techniques. © 2021 ACM.

关键词： image reconstruction

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Iterative gradient encoding network using feature co-occurrence loss for single image reflection removal 21

Iterative gradient encoding network using feature co-occurre...

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

作者： Bera, Sutanu Biswas, Prabir Kumar Indian Institute of Technology Kharagpur Kharagpur India

ISBN: (纸本)9781450391276

Removing undesired reflections from a photo taken in front of a glass is of great importance for enhancing visual computing systems' efficiency. Previous learning-based approaches have produced visually plausible results for some reflections type, however, failed to generalize against other reflection types. there is a dearth of literature for efficient methods concerning single image reflection removal, which can generalize well in large-scale reflection type. In this study, we proposed an iterative gradient encoding network for single image reflection removal. Next, to further supervise the network in learning the correlation between the transmission layer features, we proposed a feature co-occurrence loss. Extensive experiments on the public benchmark dataset of SIR2 demonstrated that our method can remove reflection favorably against the existing state of the art method on all imaging settings, including diverse backgrounds. Moreover, as the reflection strength increases, our method can still remove reflection even where other state of the art methods failed. © 2021 ACM.

关键词： Iterative methods

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Automated tree generation using grammar & particle system 21

Automated tree generation using grammar & particle system

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

作者： Jain, Aryamaan Sunkara, Jyoti Shah, Ishaan Sharma, Avinash Rajan, K.S. IIIT Hyderabad India

ISBN: (纸本)9781450391276

Trees are an integral part of many outdoor scenes and are rendered in a wide variety of computer applications like computer games, movies, simulations, architectural models, AR and VR. this has led to increasing demand for realistic, intuitive, lightweight and easy to produce computer-generated trees. the current approaches at 3D tree generation using a library of trees lack variations in structure and are repetitive. this paper presents an extended grammar-based automated solution for 3D tree generation that can model a wide range of species, both Western and indian. For the foliage, we adopt a particle system approach that models the leaf, its size, orientation and changes. the proposed solution additionally allows control for individual trees, thus modelling the tree growth variations, changes in foliage across seasons, and leaf structure. this enables the generation of virtual forests with different tree compositions. In addition, a Blender add-on has been developed for use and will be released. © 2021 ACM.

关键词： computer games

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