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检索条件"任意字段=Conference on Image and Video Communications and Processing"

共 4768 条记录，以下是11-20 订阅

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Point Cloud Color Upsampling with Attention-Based Coarse Colorization and Refinement

Point Cloud Color Upsampling with Attention-Based Coarse Col...

引用

2025 IEEE/CVF Winter conference on Applications of Computer Vision, WACV 2025

作者： Matsuzaki, Kohei Nonaka, Keisuke Kddi Research Inc. Japan

ISBN: (纸本)9798331510831

Point cloud color upsampling is an important and less explored research topic. State-of-the-art methods colorize points based on the colors of neighboring points and geometric distances. However, these methods often suffer from blurring and noise at color boundaries since object textures can have large color variations even between geometrically neighboring positions. In this paper, we propose a point cloud color upsampling method with attention weights for neighboring points. The proposed method first performs coarse colorization with the colors of low-resolution points neighboring the high-resolution points and predicted weights. Then, it refines the colors by predicting offsets for high-resolution points with aggregate features obtained from the low-resolution points. Both quantitative and qualitative experimental results on datasets acquired in real-world environments demonstrate that the proposed method achieves significantly superior color upsampling performance compared to state-of-the-art methods. © 2025 IEEE.

关键词： Color image processing

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28th International conference on image processing, Computer Vision, and Pattern Recognition, IPCV 2024, and 23rd International conference on Information and Knowledge Engineering, IKE 2024, held as part of the World Congress in Computer Science, Computer Engineering and Applied Computing, CSCE 2024

28th International Conference on Image Processing, Computer ...

引用

28th International conference on image processing, Computer Vision, and Pattern Recognition, IPCV 2024, and 23rd International conference on Information and Knowledge Engineering, IKE 2024, held as part of the World Congress in Computer Science, Computer Engineering and Applied Computing, CSCE 2024

ISBN: (纸本)9783031859328

The proceedings contain 28 papers. The special focus in this conference is on image processing, Computer Vision, and Pattern Recognition. The topics include: image-Based Seal Recognition: Approaches and Challenges in Current Automated Systems;Deep Learning Techniques for Lunar Impact Crater Identification Based on CCD and DEM Data;silicon Wafer Map Defect Classification Using Artificial Intelligence Models;low Light image Enhancement Using Autoencoder-Based Deep Neural Networks;towards Elephants Intelligent Monitoring in Zakouma National Park, Chad;a Review of Multi-modal and Multi-view Applications in Hand-Drawn Sketch images;residential Real Estate image Classification for Property Valuation;Novel Method to Investigate Decay in Rotting Bananas Using RGB Color images;lalitha: A Hand Gesture-Based Computer Control System;dishari: A Novel Gesture-Based Educational Application for Specially Challenged People;mobility Anomaly Detection with Intelligent video Surveillance;Weakly-Supervised video Anomaly Detection Using Modified Anomaly Score Module and Modified BERT;Contour Detection of Seeds Based on Traditional and Convolutional Neural Network (CNN) Based Algorithms;Early Detection of Lameness in Dairy Cattle Using Activity Data, image Analysis, AI and ML - An Approach for Improved Animal Welfare and Economic Impact;implications for Designing Hawks Detection with Data Augmentation and Network Optimizations;a Review of Detecting and Quantification of Cracks Using Convolutional Neural Networks and image processing Techniques;using Linkage Context for Automated Correction in Unsupervised Entity Resolution;the Rising Threat Against Modern Technology in Cybersecurity;an Online Bookstore Design and Implementation;cybersecurity: Sight and Foresight;the Application of Blockchain Technology in the Transmission of Semiconductor Process Recipes;the Use of Social Media and the Internet for the Facilitation of Human Trafficking.

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Weakly-Supervised video Anomaly Detection Using Modified Anomaly Score Module and Modified BERT

Weakly-Supervised Video Anomaly Detection Using Modified Ano...

引用

作者： Chen, Jun-Xiang Leou, Jin-Jang National Chung Cheng University Chiayi621 Taiwan

ISBN: (纸本)9783031859328

In this study, a weakly-supervised video anomaly detection approach using modified anomaly score module and modified BERT is proposed. The proposed approach consists of four main steps. (1) A video sequence is divided into nonoverlapping video clips and each video clip consists of sixteen adjacent video frames. (2) The video clips are fed into I3D to extract video clip feature vectors, which are fed into the proposed modified anomaly score module and the proposed modified BERT module to obtain the video clip feature vector anomaly scores and the video sequence classification anomaly score, respectively. (3) The video clip feature vector anomaly scores are multiplied by the video sequence classification score to obtain the video clip anomaly scores, which are fed into frame anomaly score production operation to obtain the video frame anomaly scores. (4) Based on the specified threshold, the video frames are determined as abnormal or normal. Based on the experimental results obtained in this study, the performance of the proposed approach is better than those of comparison approaches. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Supervised learning

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Intrusion Detection from Surveillance video Using Frame Based image processing Techniques 1st

Intrusion Detection from Surveillance Video Using Frame Base...

引用

1st International Research conference on Computing Technologies for Sustainable Development, IRCCTSD 2024

作者： Mohamed Yaseen, M.S. Radeesh, P. Chitra, P. Ramesh, Kishore SRM Institute of Science and Technology Vadapalani Tamil Nadu Chennai India

ISBN: (纸本)9783031823824

In India, the number of surveillance cameras has increased rapidly, making it challenging for law enforcement to go through the vast amount of recorded footage. We suggest a technique for quickly reviewing large amounts of video feed in order to address this issue. By utilizing sophisticated algorithms such as facial recognition, lightweight YuNet model face detection, and motion detection through background subtraction, our system accelerates the analysis of videos from various camera systems. Our model is a great tool for any agency looking to improve its operational efficiency when handling large amounts of monitoring data because it can quickly identify important events and produce concise summaries with timestamps. This piece of research contributes towards development within this field since such new methods are combined into one single solution thereby advancing surveillance technology while at the same time providing concrete benefits for everyday challenges faced by law enforcement agencies. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Intrusion detection

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Enhancing and Analyzing Log Generation for Collaborative Problem-Solving Activities: video Analysis and OCR Techniques 17th

Enhancing and Analyzing Log Generation for Collaborative Pro...

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17th Annual ACM India Compute conference, COMPUTE 2024

作者： Jadhav, Suprabha Jain, Parth Raith, Harjot Singh Arya, Kavi Iyer, Sridhar Educational Technology IIT Bombay Mumbai India Information Technology Atharva College of Engineering Malad India Artificial Intelligence and Data Science NMIMS Kharghar Navi Mumbai India Computer Science and Engineering IIT Bombay Mumbai India

ISBN: (纸本)9783031843907

This study explores the use of video analysis and Optical Character Recognition (OCR) to generate accurate logs for tracking user search behaviors for external resources during collaborative problem-solving activities on the RoboReady educational platform. The research included 15 teams of engineering students who interacted with a website designed around the PISA 2015 collaborative problem-solving framework. video recordings of the user’s screens were analyzed using image processing and OCR to extract URLs and timestamps of visited web pages. The study compares these logs with those collected through server-side tracking, noting the limitations of the latter in capturing external resource usage. The methodology includes frame extraction, URL isolation, and text recognition using Tesseract OCR and Google Cloud Vision API. Challenges like noisy OCR output and the necessity for manual verification are addressed. The generated logs provide insights into user’s navigation and resource usage. However, limitations such as video quality dependency, scalability issues, and the need for manual intervention are also discussed. This research enhances the understanding of user’s behavior in online learning environments and offers methodological insights for studying digital learning interactions. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： video analysis

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Mobility Anomaly Detection with Intelligent video Surveillance 28th

Mobility Anomaly Detection with Intelligent Video Surveillan...

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作者： Ebrahimi, Fatemeh Rousseau, Jacqueline Meunier, Jean Department of Computer Science and Operations Research University of Montreal Montreal Canada School of Rehabilitation University of Montreal Montreal Canada

ISBN: (纸本)9783031859328

This paper outlines a study aimed at enhancing elderly care through an intelligent video surveillance system that leverages deep learning for detecting mobility anomalies, specifically near-falls. Identifying near-falls is essential because people who experience frequent near-falls while carrying out their daily activities are at risk of future falls. We successfully developed an autoencoder to detect these anomalies, particularly near-falls, by identifying high reconstruction errors throughout five consecutive frames. To extract a person's skeleton, we utilized MoveNet and narrowed it down to only seven keypoints. We then used a set of 20 features, encompassing joint positions, velocities, accelerations, angles, and angular accelerations, to train the model. Our model was tested on 100 videos of simulated daily activities recorded in an apartment laboratory, where 50 of them contained a near-fall. Results show that our model can successfully detect near-falls with 90% sensitivity, specificity, and accuracy, highlighting its potential to enhance elderly care in their living environments. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Fall detection

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Proceedings of image and video communications and processing 2003

Proceedings of Image and Video Communications and Processing...

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image and video communications and processing 2003

This Volume 5022 part 2 of 2 parts of the conference proceedings contains 56 papers. Topics discussed include video scaling, image coding, image/video processing, media processors, image/video content analysis and ret... 详细信息

关键词： image communication systems

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2014 IEEE Visual communications and image processing conference, VCIP 2014

2014 IEEE Visual Communications and Image Processing Confere...

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2014 IEEE Visual communications and image processing conference, VCIP 2014

ISBN: (纸本)9781479961399

The proceedings contain 139 papers. The topics discussed include: studying the added value of computational saliency in objective image quality assessment;foveation-based image quality assessment;a novel objective quality assessment method for perceptual video coding in conversational scenarios;optimized spatial and temporal resolution based on subjective quality estimation without encoding;blind image quality assessment based on a new feature of nature scene statistics;image transformation using limited reference with application to photo-sketch synthesis;a novel metric for efficient video shot boundary detection;hybrid modeling of natural image in wavelet domain;discriminative multi-modality non-negative sparse graph model for action recognition;and intrinsic flexibility exploiting for scalable video streaming over multi-channel wireless networks.

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Deep Fake video Detection Using Transfer Learning Techniques 6th

Deep Fake Video Detection Using Transfer Learning Techniques

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6th International conference on Advanced Informatics for Computing Research, ICAICR 2023

作者： Anuhya, Karampuri Shivaram, D. Karthikeya, Deekonda Jyothi, B.N. Jabbar, M.A. Akhtar, Zahid Vardhaman College of Engineering Kacharam Shamshabad India State University of New York Polytechnic Institute Marcy United States

ISBN: (纸本)9783031840586

Deep Fakes are now a concern and a threat to society as they are mostly misused for creating chaos and are tools of crimes. There are many software that can create the most realistic deep fakes in a matter of seconds using image processing and deep learning techniques. This work deals with and adapts transfer learning techniques for the detection of deep fake videos. It also proposes the ensemble model advantages for better judgment. The FaceForensics++ dataset which consists of FaceSwap, Face2Face, NeuralTextures, DeepFakes, and small portions of them are used for training three different transfer learning models VGG19, EfficientNetB5, and InceptionResNetV2. The ensemble model of these is used to finally communicate the results. The results obtained individual model-wise as well as ensemble of the same has been observed as part of this work. The detection accuracy of InceptionResNetV2 is 96.74% whereas the ensemble model is 65% for the same samples and training parameters. The results of our work indicate that adaptation of transfer learning is a good sign for deep fake video detection and it performs better when trained with large amounts of heterogenous datasets. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Contrastive Learning

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2024 IEEE International conference on Visual communications and image processing, VCIP 2024

2024 IEEE International Conference on Visual Communications ...

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2024 IEEE International conference on Visual communications and image processing, VCIP 2024

ISBN: (纸本)9798331529543

The proceedings contain 139 papers. The topics discussed include: cross-device image saliency detection: database and comparative analysis;performance evaluation of feature detectors and descriptors with close-range solar panel images;inter Submesh border information coding with skip mode in V-DMC;advancements in Lenslet video coding: insights from MPEG LVC;advanced learning-based inter prediction for future video coding;packed regions information SEI message;content-adaptive rate-quality curve prediction model in media processing system;deep reinforcement learning-based camera autofocus with gaussian process regression;and frame similarity-based screen content video quality enhancement via adaptive long short-term fusion.

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