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检索条件"任意字段=15th Indian Conference on Computer Vision, Graphics and Image Processing, ICVGIP 2024"

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Proceedings of icvgip 2024 - 15th indian conference on computer vision, graphics and image processing

Proceedings of ICVGIP 2024 - 15th Indian Conference on Compu...

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15th indian conference on computer vision, graphics and image processing, icvgip 2024

ISBN: (纸本)9798400710759

the proceedings contain 49 papers. the topics discussed include: enhancing face quality assessment through age and expression analysis;IDA-UIE: an iterative framework for deep network based degradation aware underwater image enhancement;an improved framework for precision grading of renal cell carcinoma using histopathological images;lost in context: the influence of context on feature attribution methods for object recognition;vision-language modeling with regularized spatial transformer networks for all weather crosswind landing of aircraft;on the efficacy of guidance tasks in panoptic segmentation;enhancing generalization ability in deepfake detection via continual learning;and a computer vision framework on biomechanical analysis of jump landings.

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Exploration of Gesture-Based Text Input System for Indic Languages 15th

Exploration of Gesture-Based Text Input System for Indic Lan...

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15th indian conference on Human-computer Interaction Design and Research

作者： Das, Amrita Natl Inst Design Gandhinagar India

ISBN: (纸本)9783031808319;9783031808326

Many innovative text input methods exist but are scarce in indian languages. In this paper, we aim to explore a novel text input method for the Malayalam language. this method is gesture-based, where specific hand movements using the natural demarcations of the hand are mapped to particular characters, which enables typing. this is implemented using an image processing program to track key points on our hands, which allows us to distinguish between different gestures accurately. We conducted a study to identify which gestures provide higher accuracy, and least confusion. Using the results, we mapped the gestures to Malayalam and conducted an empirical longitudinal study, which analyzed the speed and accuracy of this prototype. this method yielded a 40+ CPM, which is comparable to similar text input studies in other languages. this technology can be further developed to assist users in various ways, such as providing a communication guide or aiding in daily activities.

关键词： Indic Text Input computer vision Longitudinal Study

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Spectrogrand: Computational Creativity Driven Audiovisuals' Generation From Text Prompts 24

Spectrogrand: Computational Creativity Driven Audiovisuals' ...

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15th indian conference on computer vision graphics and image processing

作者： Jaisankar, Vijay Jayagopi, Dinesh Babu Int Inst Informat Technol Bangalore Bangalore Karnataka India

ISBN: (纸本)9798400710759

We explore the applicability of spectrograms in Deep learning applications and in guiding creative decisions. To this end, we propose Spectrogrand, a novel spectrogram-driven end-to-end Generative AI pipeline creating interesting audiovisuals from text prompts and incorporating lightweight computational creativity metrics. this process involves selecting a music piece to underpin the audiovisual, generating an album cover image for the music, and performing neural style transfer on spectrogram chunks to generate the frames for the audiovisual. To democratise the benefits of this pipeline, we open-source the tool, computational creativity metrics, and associated data (1).

关键词： Computational creativity Generative AI Audiovisual generation Spectrograms computer vision

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Internal Embeddings of Multi-modal LLMs as Generalizable Representations for image Quality Assessment 24

Internal Embeddings of Multi-modal LLMs as Generalizable Rep...

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15th indian conference on computer vision graphics and image processing

作者： Totade, Sanjot Sagar Babu, Nithin C. Rao, Shika Soundararajan, Rajiv Indian Inst Sci Bangalore Elect Commun Engn Bangalore Karnataka India

ISBN: (纸本)9798400710759

One of the major challenges in no-reference (NR) image quality assessment (IQA) is the ability to generalize to diverse quality assessment applications. Recently, multi-modal vision-language models are found to be very promising in this direction. they are beginning to form a part of several state of the art NR IQA methods. On the other hand, multi-modal large language models (LLMs) are increasingly being studied for various computer vision applications including IQA. In this work, we perform a thorough study of the ability of multi-modal LLMs for NR IQA by training some of its components and testing for its generalizability. In particular, we keep the LLM frozen and learn parameters corresponding to the querying transformer, LLM prompt and some layers that process the embedding output by the LLM. We observe that some of these components offer a generalization performance far superior to any existing NR IQA algorithm.

关键词： image quality assessment large language models

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A computer vision Framework on Biomechanical Analysis of Jump Landings 24

A Computer Vision Framework on Biomechanical Analysis of Jum...

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15th indian conference on computer vision graphics and image processing

作者： Sharma, Srishti U. Divakaran, Srikrishnan Kaya, Tolga Raval, Mehul S. Ahmedabad Univ Sch Engn & Appl Sci Amdavad Gujarat India Krea Univ Sri City India Sacred Heart Univ Fairfield CT USA Ahmedabad Univ Amdavad India

ISBN: (纸本)9798400710759

High-intensity activities in sports like basketball can result in fatigue without proper recovery. this study introduces a collaborative framework that leverages computer vision (CV) and Machine Learning for evaluating jump landings and predicting athletic readiness by modelling Countermovement Jumps (CMJs) biomechanical aspects. Seventeen female collegiate basketball athletes of Sacred Heart University (SHU), CT, USA, participated in weekly CMJs over a 26-week season. through CV-driven semantic analysis of videos, the framework identifies the crucial initial contact and maximum flexion point during jump landings and extracts kinetic and kinematic features of the lower extremities. Next, an inferential analysis is conducted to understand the relationship between these features and the CMJ-driven reactive strength indexmodified (RSImod) score, which measures fatigue and athletic readiness. An XGBoost regressor, trained on the past week's data, then predicted the RSImod score for the following week, which resulted in an MSE of 0.020 and an R-2 of 0.892. Using SHapley Additive exPlanations (SHAP), the framework offers interpretable feedback, aiding coaches in creating personalised training programs and optimising athletic performance while minimising injury risks.

关键词： Athletes basketball computer vision countermovement jumps sports analytics

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Pick and Pack: revitalizing mandalas through digital artistry 24

Pick and Pack: revitalizing mandalas through digital artistr...

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15th indian conference on computer vision graphics and image processing

作者： Sarkar, Tusita Abhishek, Tushar Bhowmick, Partha Indian Inst Technol Kharagpur Dept Comp Sci & Engn Kharagpur W Bengal India

ISBN: (纸本)9798400710759

this paper presents a novel approach to computational art focusing on mandalas-an iconic heritage of indian art that has proliferated significantly in recent times. Our innovative software allows users to input a handcrafted mandala and select specific motifs for error rectification. the rectification leverages vector information for geometric discretization alongside a simple GCD rule, adhering to traditional mandala principles. the rectified image, being in vector form, allows various real-time operations in the vector space, such as insertion, deletion, or modification of motifs or layers, facilitating enhancements, enlargements, or creation of new compositions. We demonstrate the software's merit and versatility through various examples, highlighting its potential for special applications such as digital artistry with mandalas, including teaching and training. this work not only advances the field of computational art but also promises to preserve and enhance the rich tradition of mandala art through modern technology.

关键词： Art and culture art and psychology computational art digital art indian art mandala

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Leveraging Auxiliary Classification for Rib Fracture Segmentation 24

Leveraging Auxiliary Classification for Rib Fracture Segment...

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15th indian conference on computer vision graphics and image processing

作者： Harini, G. Farooq, Aiman Mishra, Deepak Indian Inst Technol Jodhpur Jodhpur Rajasthan India

ISBN: (纸本)9798400710759

thoracic trauma often results in rib fractures, which demand swift and accurate diagnosis for effective treatment. However, detecting these fractures on rib CT scans poses considerable challenges, involving the analysis of many image slices in sequence. Despite notable advancements in algorithms for automated fracture segmentation, the persisting challenges stem from the diverse shapes and sizes of these fractures. To address these issues, this study introduces a sophisticated deep-learning model with an auxiliary classification task designed to enhance the accuracy of rib fracture segmentation. the auxiliary classification task is crucial in distinguishing between fractured ribs and negative regions, encompassing non-fractured ribs and surrounding tissues, from the patches obtained from CT scans. By leveraging this auxiliary task, the model aims to improve feature representation at the bottleneck layer by highlighting the regions of interest. Experimental results on the RibFrac dataset demonstrate significant improvement in segmentation performance.

关键词： Rib Fracture Attention Weak Supervision Segmentation

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Dementia Disease Progression Analysis from 2D Cellular Automata Architecture 24

Dementia Disease Progression Analysis from 2D Cellular Autom...

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15th indian conference on computer vision graphics and image processing

作者： Kesu, Siva Manohar Reddy Sinha, Neelam Ramasangu, Hariharan Inst Sci Campus Ctr Brain Res Indian Bangalore Karnataka India Relecura Bangalore Karnataka India

ISBN: (纸本)9798400710759

the detection of change in mild cognitive impairment (MCI) is vital between one visit and another visit for the early-stage detection of Alzheimer's disease (AD). It is associated with changes in the structural and functional aspects. Diagnosis of dementia progression is a challenging but essential step for the planning of early treatment. this paper proposes the cellular automata (CA) framework to identify the changes when the disease progresses from one visit to another. An updated rule using the conduction function of anisotropic diffusion has been proposed to assess the earliest signs of dementia manifestation and progression. the progression of dementia disease in multi-visit subjects for healthy and unhealthy patients has been analyzed by examining the entropy from evolved 2D CA images. the subjects below the reference line in healthy cases lead to the prognosis of the disease, whereas subjects above the reference line in unhealthy subjects are in improved condition. the proposed CA architecture shows the transitions and progressive patterns, thereby offering a method for tracking the evolution of dementia over time.

关键词： Dementia Functional Connectivity FMRI Cellular Automata Disease Progression

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MoCoMER: A Self Supervised Representation Learning for Handwritten Mathematical Expression Recognition 24

MoCoMER: A Self Supervised Representation Learning for Handw...

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15th indian conference on computer vision graphics and image processing

作者： Pramanik, Sandip Mitra, Shree Das, Nibaran Jadavpur Univ Dept CSE Kolkata W Bengal India Indian Inst Informat Technol Guwahati Gauhati India

ISBN: (纸本)9798400710759

this paper presents a self-supervised learning (SSL) based framework, specifically designed for Handwritten Mathematical Expression Recognition (HMER). the proposed approach incorporates a momentum encoding technique and a non-linear projection head into the image encoder to effectively address the common issue of dimensional collapse in self-supervised learning (SSL) methods. Our approach consists of two main steps: first, we use self-supervised pre-training to train the image encoder to obtain strong feature representations from HME images. Subsequently, we fine-tune the model using a Transformer network to predict LaTeX sequences from HME images. the assessment demonstrates that our SSL framework surpasses other existing SSL frameworks as well as several supervised methods in terms of performance. the findings indicate that our approach is highly advanced, emphasizing its potential to enhance the robustness and efficiency of feature representations in HMER tasks. the integration of momentum encoding and a non-linear projection head in the image encoder is shown to enhance the durability and effectiveness of feature representations, leading to superior performance in HMER tasks. Our experiments reveal that our approaches achieve an expression recognition rate (ExpRate) of 62. 17%, 61. 03%, 64. 8% on the CROHME 2014,2016,2019 test datasets respectively. the CROHME 2019 test data achieves the highest ExpRate, which is state-of-the-art (SOTA). this success is achieved by overcoming the challenges of dimensional collapse and leveraging the advantages of both self-supervised and supervised learning.(1)

关键词： HMER SSL Contrastive Learning Momentum Contrast (MoCo) Non-linear projection head Transformer

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A biologically inspired saliency model for color fundus images 16

A biologically inspired saliency model for color fundus imag...

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

作者： Rangrej, Samrudhdhi B. Sivaswamy, Jayanthi IIIT Hyderabad CVIT Hyderabad Andhra Pradesh India

ISBN: (纸本)9781450347532

Saliency computation is widely studied in computer vision but not in medical imaging. Existing computational saliency models have been developed for general (natural) images and hence may not be suitable for medical images. this is due to the variety of imaging modalities and the requirement of the models to capture not only normal but also deviations from normal anatomy. We present a biologically inspired model for colour fundus images and illustrate it for the case of diabetic retinopathy. the proposed model uses spatially varying morphological operations to enhance lesions locally and combines an ensemble of results, of such operations, to generate the saliency map. the model is validated against an average Human Gaze map of 15 experts and found to have 10% higher recall (at 100% precision) than four leading saliency models proposed for natural images. the F-score for match with manual lesion markings by 5 experts was 0.4 (as opposed to 0.532 for gaze map) for our model and very poor for existing models. the model's utility is shown via a novel enhancement method which employs saliency to selectively enhance the abnormal regions and this was found to boost their contrast to noise ratio by similar to 30%.

关键词： Colour fundus image diabetic retinopathy (DR) saliency spatially-varying morphology gaze map selective-enhancement

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