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检索条件"任意字段=Intelligent Robotics and Industrial Applications using Computer Vision 2017, IRIACV 2017"

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intelligent robotics and industrial applications using computer vision 2024

Intelligent Robotics and Industrial Applications Using Compu...

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IS and T International Symposium on Electronic Imaging 2024: intelligent robotics and industrial applications using computer vision, iriacv 2024

The proceedings contain 34 papers. The topics discussed include: extending lidar depth range using stereo depth estimation on intensity data;transformers for microscopy slide image segmentation of invasive melanoma;intracell capacitances in pixel-level hybrid bond image sensor cells;self-attention enhanced recognition: a unified model for handwriting and scene-text recognition with improved inference;evaluation of subjective video quality of television displays;experimental study on reducing wavelength dependency of spatial resolution characteristics of a digital camera by MTF correction;comparative analysis of user experience in virtual reality (VR) and mixed reality (MR) systems using eye-tracking measurements;RAIV: researchable archives for interactive visualizations;mobile 3D mapping of Erdstall facilities;real-time stereoscopic image-parallel path tracing;automatic reading order sequencing: a novel reading order generator for text-based documents;and improving video deepfake detection: a DCT-based approach with patch-level analysis.

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intelligent robotics and industrial applications using computer vision 2023

Intelligent Robotics and Industrial Applications using Compu...

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IS and T International Symposium on Electronic Imaging: intelligent robotics and industrial applications using computer vision, iriacv 2023

The proceedings contain 174 papers. The topics discussed include: appearance segmentation and documentation applied to cultural heritage surfaces;end-to-end evaluation of practical video analytics systems for face detection and recognition;testing the role of vision spatial processing in color deficiency;a lightweight exposure bracketing strategy for HDR imaging without access to camera raw;style transfer for improved visualization of underdrawings and ghost paintings: an application to a work by Vincent van Gogh;tangible extended reality with sensor fusion;orca: an end-to-end video object removal framework with cropping interested region and quality assessment;simulation and design of a burst mode 20mfps global shutter high conversion gain CMOS image sensor in a standard 180nm CMOS image sensor process using sequential transfer gates;3D joist perception, detection, and climbing for hexapod robot;synthetic speech attribution using self-supervised audio spectrogram transformer;incidence of stereo blindness in a recent VR distance perception user study;mesh distance for dimension reduction and visualization of numerical simulation data;and teaching color science to EECS students using interactive tutorials: tools and lessons.

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intelligent robotics and industrial applications using computer vision 2022

Intelligent Robotics and Industrial Applications using Compu...

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IS and T International Symposium on Electronic Imaging: intelligent robotics and industrial applications using computer vision, iriacv 2022

The proceedings contain 154 papers. The topics discussed include: feature-driven 3d range geometry compression via spatially-aware depth encoding;open source deep learning inference libraries for autonomous driving systems;problems in image target-based color correction;improvement of aerial image by simulations;recognition-aware learned image compression;artist-specific style transfer for semantic segmentation of paintings: the value of large corpora of surrogate artworks;data visualization of crime data using immersive virtual reality;a comparison of non-experts and experts using DSIS method;contrast enhancement: cross-modal learning approach for medical images;a continuous bitstream-based blind video quality assessment using multi-layer perceptron;correspondences for image and video reconstruction;design and analysis on low-power and low-noise single slope ADC for digital pixel sensors;incremental two-network approach to develop a purity analyzer system for canola seeds;advantage of machine learning over maximum likelihood in limited-angle low-photon x-ray tomography;image montage detection based on image segmentation and robust hashing techniques;chatbot integrated with machine learning deployed in the cloud and performance evaluation;and the relationship between vision and simulated remote vision system air refueling performance.

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intelligent robotics and industrial applications using computer vision 2021

Intelligent Robotics and Industrial Applications using Compu...

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2021 intelligent robotics and industrial applications using computer vision Conference, iriacv 2021

The proceedings contain 166 papers. The topics discussed include: data visualization and analysis of playing styles in tennis;crosstalk minimization method for eye-tracking-based 3D display;detecting deepfakes with Haralick’s texture properties;turkey behavior identification system with a GUI using deep learning and video analytics;projection methods for finding intersection of two convex sets and their use in signal processing problems;high-speed inline computational imaging for area scan cameras;interdisciplinary immersive experiences within artistic research, social and cognitive sciences;a single chip PPG sensor with enhanced IR sensitivity for low power and small size;single chip auto-valet parking system with TDA4VMID SoC;boosting computer vision performance by enhancing camera ISP;transfer learning with style transfer between the photorealistic and artistic domain;knowledge distillation from multispectral images for fish freshness estimation;next best light position: a self-configuring approach for the reflectance transformation imaging acquisition process;experimental study for revising visual noise measurement of ISO 15739;and computational identification of significant actors in paintings through symbols and attributes.

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intelligent robotics and industrial applications using computer vision 2020

Intelligent Robotics and Industrial Applications using Compu...

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2020 intelligent robotics and industrial applications using computer vision Conference, iriacv 2020

The proceedings contain 283 papers. The topics discussed include: a new training model for object detection in aerial images;managing crops across spatial and temporal scales - the roles of UAS and satellite remote sensing;a gaze-contingent system for foveated multiresolution visualization of vector and volumetric data;capturing and 3D rendering of optical behavior: the physical approach to realism;tereoscopic 3D optic flow distortions caused by mismatches between image acquisition and display parameters (JIST-first);active shooter response training environment for a building evacuation in a collaborative virtual environment;learning a CNN on multiple sclerosis lesion segmentation with self-supervision;reducing invertible embedding distortion using graph matching model;creating high-resolution 360-degree single-line 25k video content for modern conference rooms using film compositing techniques;spectral reproduction: drivers, use cases and workflow;SPECTRANET: a deep model for skin oxygenation measurement from multi-spectral data;automotive image quality concepts for the next SAE levels: color separation and contrast detection probability;a 4-tap global shutter pixel with enhanced IR sensitivity for VGA time-of-flight CMOS image sensors;small object bird detection in infrared drone videos using mask R-CNN deep learning;real-world fence removal from a single-image via deep neural network;and perceptual quality assessment of enhanced images using a crowd-sourcing framework.

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intelligent robotics and industrial applications using computer vision 2019

Intelligent Robotics and Industrial Applications Using Compu...

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2019 intelligent robotics and industrial applications using computer vision Conference, iriacv 2019

The proceedings contain 269 papers. The topics discussed include: high-speed multiview 3D structured light imaging technique;integration of advanced stereo obstacle detection with perspectively correct surround views;recreating Van Gogh's original colors on museum displays;modeling long range features from serial section imagery of continuous fiber reinforced composites;the quality of stereo disparity in the polar regions of a stereo panorama;do different radiologists perceive medical images the same way? some insights from representational similarity analysis;the intersection of artificial intelligence and augmented reality;self-calibrated surface acquisition for integrated positioning verification in medical applications;gradient management and algebraic reconstruction for single image super resolution;segmentation-based detection of local defects on printed pages;automated optical inspection for abnormal-shaped packages;towards combining domain knowledge and deep learning for computational imaging;a 360-degrees holographic true 3D display unit using a Fresnel phase plate;and visual analytic process to familiarize the average person with ways to apply machine learning.

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Visual Odometry and Mapping under poor Visibility Conditions using a Stereo Infrared Thermal Imaging System

Visual Odometry and Mapping under poor Visibility Conditions...

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IS and T International Symposium on Electronic Imaging: intelligent robotics and industrial applications using computer vision, iriacv 2023

作者： Edlinger, Raimund Himmelbauer, Gabriel Zauner, Gerald Nüchter, Andreas University of Applied Sciences Upper Austria Wels Austria Informatics XVII - Robotics Julius-Maximilians University Würzburg Germany

In the past decades, developments in the field of computer vision have made both the software and hardware more capable and more easily accessible. This has enabled otherwise complex vision systems to be used in other fields, such as autonomous robotics. Although image processing systems in the visible light spectrum are commonplace in robotics today, the IR spectrum is still rarely used, although it offers certain advantages. A thermal camera can sense the temperature of objects, is independent of illumination and can actually see through heavy smoke and fog. This makes it a useful tool in particular in the field of rescue robotics, where poor vision conditions are to be expected. In this paper, the feasibility of using two thermal cameras in a stereo vision setup to map indoor scenes is to be examined. It is meant to allow an autonomous robot to perceive its indoor surroundings as a 3D space, even in poor vision conditions. The biggest challenges are the calibration of thermal cameras and the proper filtering of the raw image and the resulting disparity map. Simple and easily implemented solutions are proposed for each of these issues. © 2023, Society for Imaging Science and Technology.

关键词： Stereo vision

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Synthetic Data Generation for AI-based Machine vision applications

Synthetic Data Generation for AI-based Machine Vision Applic...

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IS and T International Symposium on Electronic Imaging 2024: intelligent robotics and industrial applications using computer vision, iriacv 2024

作者： Seiler, Frederik Eichinger, Verena Effenberger, Ira Fraunhofer IPA Stuttgart Germany

This paper presents a method for synthesizing 2D and 3D sensor data for various machine vision tasks. Depending on the task, different processing steps can be applied to a 3D model of an object. For object detection, segmentation and pose estimation, random object arrangements are generated automatically. In addition, objects can be virtually deformed in order to create realistic images of non-rigid objects. For automatic visual inspection, synthetic defects are introduced into the objects. Thus sensor-realistic datasets with typical object defects for quality control applications can be created, even in the absence of defective parts. The simulation of realistic images uses physically based rendering techniques. Material properties and different lighting situations are taken into account in the 3D models. The resulting tuples of 2D images and their ground truth annotations can be used to train a machine learning model, which is subsequently applied to real data. In order to minimize the reality gap, a random parameter set is selected for each image, resulting in images with high variety. Considering the use cases damage detection and object detection, it has been shown that a machine learning model trained only on synthetic data can also achieve very good results on real data. © 2024, Society for Imaging Science and Technology.

关键词： Object detection

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Real-time Cattle Intake Monitoring using Stereo vision

Real-time Cattle Intake Monitoring using Stereo Vision

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IS and T International Symposium on Electronic Imaging 2024: intelligent robotics and industrial applications using computer vision, iriacv 2024

作者： Rao, Prajwal Flinders, McKinley N. Buckmaster, Dennis Reibman, Amy R. Boerman, Jacquelyn P. Elmore Family School of Electrical and Computer Engineering Purdue University West Lafayette United States Department of Animal Sciences Purdue University West Lafayette United States Agriculture and Biological Engineering Purdue University West Lafayette United States

Accurate measurements of daily feed consumption for dairy cattle is an important metric for determining animal health and feed efficiency. Traditionally, manual measurements or average feed consumption for groups of animals have been employed which leads to human error and overall inconsistent measurements for the individual. Therefore, we developed a scalable non-invasive analytics system that leverages depth information derived from stereo cameras to consistently measure feed offered and report findings throughout the day. A top-down array of cameras faces the available feed, measures feed depth, projects depth to a 3-dimensional (3D) mesh, and finally estimates feed volume from the 3D projection. Our successful experiments at the Purdue University Dairy, that houses 230 cows, demonstrates its robustness and scalability for larger operations holding significant potential for optimizing feed management in dairy farms, thereby improving animal health and sustainability in the dairy industry. © 2024, Society for Imaging Science and Technology.

关键词： Stereo vision

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Unsupervised PCB Anomaly Segmentation with Foundational Models

Unsupervised PCB Anomaly Segmentation with Foundational Mode...

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IS and T International Symposium on Electronic Imaging 2024: intelligent robotics and industrial applications using computer vision, iriacv 2024

作者： Ho, Chih-Hui Seo, SungBal Kim, NaYeon Wu, Pin-Ying Bae, YouSuk Vasconcelos, Nuno Department of Electrical and Computer Engineering University of California San Diego United States Department of Computer Engineering Tech University of Korea Korea Republic of

PCB defect segmentation aims to localize the defects in printed circuit boards (PCBs). While this problem has a great industrial impact, few datasets are publicly available. It is also challenging to predict the defects that appear during manufacturing. To address the former challenge, we curate a large dataset with various defective categories of imbalanced distribution, reflecting real-world conditions. The problem of unsupervised PCB anomaly segmentation (UAS), where no labeled defect data is available during training, is then investigated. We propose an efficient prompt tuning method to address PCB-UAS. Specifically, a pretrained large foundational segmentation model (SAM) is adapted to PCB-UAS by the introduction of a few learnable adapter layers. SAM is frozen during training and only the additional adapter parameters are learned. To overcome the lack of labeled defect images for training, we propose to create synthetic defect images that mimic the real ones. Experiments highlight that the proposed method can outperform baselines by 7 points with 16.6 times less learnable parameters. © 2024, Society for Imaging Science and Technology.

关键词： Defects

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