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

共 128 条记录，以下是21-30 订阅

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Tailored photometric stereo: Optimization of light source positions for various materials

Tailored photometric stereo: Optimization of light source po...

引用

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

作者： Kapeller, Christian Antensteiner, Doris Štolc, Svorad AIT Austrian Institute of Technology GmbH High Performance Vision Vienna1210 Austria Vienna University of Technology Institute of Visual Computing Vienna1040 Austria

industrial machine vision applications frequently employ Photometric Stereo (PS) methods to detect fine surface defects on objects with challenging surface properties. To achieve highly precise results, acquisition setups with a vast amount of strobed illumination angles are required. The time-consuming nature of such an undertaking renders it inapt for most industrial applications. We overcome these limitations by carefully tailoring the required light setup to specific applications. Our novel approach facilitates the design of optimized acquisition setups for inline PS inspection systems. The optimal positions of light sources are derived from only a few representative material samples without the need for extensive amounts of training data. We formulate an energy function that constructs the illumination setup which generates the highest PS accuracy. The setup can be tailored for fast acquisition speed or cost efficiency. A thorough evaluation of the performance of our approach will be given on a public data set, evaluated by the mean angular error (MAE) for surface normals and root mean square (RMS) error for albedos. Our results show, that the obtained optimized PS setups can deliver a reconstruction performance close to the ground truth, while requiring only a few acquisitions. © 2020 Society for Imaging Science and Technology.

关键词： Light sources

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An image processing based method for chewing detection using Variable-intensity template

An image processing based method for chewing detection using...

引用

intelligent robotics and industrial applications using computer vision 2018, iriacv 2018

作者： Fujimoto, Atsuto Ohkawauchi, Takaaki Yamato, Junji Ohya, Jun Department of Modern Mechanical Engineering Waseda University Tokyo Japan

To contribute to the actualization of the care worker assistance robot, this paper proposes a method for detecting whether the care receiver is chewing from the video sequence acquired by the camera that observes that receiver. The proposed method detects the receiver's face and areas for both cheeks and chin. After applying some normalization to the areas, chewing detection that uses a variable-intensity template is performed, where the template consists of shape models, interest points and intensity distribution model. A likelihood based on the variableintensity template is computed so that the receiver is judged whether the receiver is chewing. Experiments using seven subjects are conducted. As a result, the accuracy of chewing detection by the proposed method is 83%, which is quite promising. © 2018, Society for Imaging Science and Technology.

关键词： Image processing

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Crowd congestion detection in videos

Crowd congestion detection in videos

引用

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

作者： Khan, Sultan Daud Mahmud, Maqsood Ullah, Habib Ullah, Mohib Cheikh, Faouzi Alaya College of Computer Science and Engineering University of Ha'il Saudi Arabia Department of Management Information System University of Imam Abdulrahman Bin Faisal Dammam Saudi Arabia Department of Computer Science Norwegian University of Science and Technology Norway

Automatic detection of crowd congestion in high density crowds is a challenging problem, with substantial interest for safety and security applications. In this paper, we propose a method that can automatically identify and localize congested regions in crowded videos. Our proposed method is based on the notion that pedestrians in the congested region follow a particular behavior. Pedestrians in the congested areas cannot move freely due to space unavailability and tend to undergo lateral oscillations. In our method, we first extract trajectories by using particle advection technique and then compute oscillatory features for each trajectory. Trajectories with higher oscillation values and with less proximity are clustered, indicating the congested regions. We perform experiments on a diversity of challenging scenarios. From the experimental results, we show that our method provides precise localization of congested regions in crowd videos. © 2020 Society for Imaging Science and Technology. All rights reserved.

关键词： Anomaly detection

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High-precision 3D sensing with hybrid light field & photometric stereo approach in multi-line scan framework

High-precision 3D sensing with hybrid light field & photomet...

引用

intelligent robotics and industrial applications using computer vision 2017, iriacv 2017

作者： Antensteiner, Doris Štolc, Svorad Valentín, Kristián Blaschitz, Bernhard Huber-Mörk, Reinhold Pock, Thomas AIT Austrian Institute of Technology GmbH Vision Automation and Control Vienna Austria Graz University of Technology Institute for Computer Graphics and Vision Graz Austria

We present a hybrid multi-line scan approach which enables simultaneous acquisition of light field & photometric stereo data. While light fields capture mostly large-scale surface deviations and rely on visible surface structures, photometric stereo is primarily sensitive to fine surface deviations and does not rely on visible structures. The combination of both approaches yields a solid performance for a large variety of depths, ranging from macro-to microscopic scales. Contrary to traditional photometric stereo, that relies on a strobed illumination, our approach uses two constant light sources which, however, generate multiple illumination geometries in different portions of the camera's field of view. Our object is moving on a conveyor belt during the acquisition process. Due to our multi-line scan sensor the object is observed from several viewing angles. The object's movement is causing each object point to be illuminated under several illumination directions. Hence, during our acquisition process the object points are captured under all feasible viewing angles and lighting conditions. In our system, surface normals are derived making use of the Lambert's cosine law. However, due to the lack of illuminations spanning orthogonally to the transport direction, the surface normals can be inferred only in the transport direction. We present a variational approach for 3D depth reconstruction designed specifically for our hybrid setup that jointly takes into account the light field as well as photometric stereo depth cues and provides one globally consistent solution. Depth maps obtained by the proposed algorithm show both the large-scale accuracy as well as sensitivity to fine surface details. © 2017, Society for Imaging Science and Technology.

关键词： Light sources

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Featureless-Region-Based top window recognition for automatic industrial monitoring systems

Featureless-Region-Based top window recognition for automati...

引用

intelligent robotics and industrial applications using computer vision 2018, iriacv 2018

作者： Ho, Mei-Hsuan Tsai, Yu-Hsuan Hsu, Chang-Tao Chuang, Ren-Hui Dept. of Computer Science and Information Engineering National Chaio Tung University Taiwan

As a vital part for industrial automatic monitoring systems, this paper presents the algorithm for top window recognition on screen-grabbed images. For better performance in terms of accuracy, efficiency, and robustness, we introduce a novel, background-based image feature of window region, i.e., locallymaximum uniform blocks extracted from regions of uniform color, to represent the practically unique spatial structure of background regions in different windows. The recognition procedure consists of several rather simple steps, c.f., foreground-based methods, which include (i) edge extraction, (ii) uniform block extraction, (iii) uniform block matching. The template window with highest matching score is then identified the top window, with its location determined simultaneously to facilitate further analysis of window content. Experimental results indicate that the proposed approach can achieve perfect recognition results for realistic image data from the industry, and also fulfill the near real-time processing requirement of on-line monitoring tasks. © 2018, Society for Imaging Science and Technology.

关键词： Extraction

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using artificial intelligence to provide visual feedback for golf swing training

Using artificial intelligence to provide visual feedback for...

引用

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

作者： Liu, Jen-Jui Newman, Jacob Lee, Dah-Jye Brigham Young University ProvoUT United States

Golf players spend hours perfecting their swing. It takes much practice and dedicated effort to train their body to make an effective swing. In order to train the body in such a way, golf players must be extremely mindful about the placement and motion of key body parts, such as wrists, elbows, shoulders, and torso. With correct placement and motion of key body parts, golf players can achieve great accuracy and consistency in their swings. In this research, we build on our previous work in evaluating the quality of a golf swing. using a deep neural network, we are able to analyze a golf swing video, determine if it was an effective or ineffective swing, and provide feedback about the specific body parts that need improvement. This feedback can be used to improve player performance. using this system consistently, a golf player can train their muscles and swinging technique. © 2021, Society for Imaging Science and Technology.

关键词： Golf

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Detecting Falling Rocks by Estimating Excavation Points using Single Color Markers

Detecting Falling Rocks by Estimating Excavation Points Usin...

引用

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

作者： Kobayashi, Rei Sato, Yoshihiro Miura, Masaya Osada, Yuto Bao, Yue Graduate School of Integrative Science and Engineering Tokyo City University 1-28-1 Tamadutsumi Setagaya-ku Tokyo Japan Tokyu Construction Co. Ltd. Sibuyatikatetubiru 1-16-14 Sibuya Sibuya-ku Tokyo Japan

Tunnels have been constructed in various places for transportation and lifelines. During tunnel construction, the industrial accidents have occurred due to falling rocks from the tunnel face. A large amount of falling rocks is confirmed in the precursor of tunnel collapse. Therefore, it is necessary to detect falling rocks to prevent industrial accidents and to grasp of the situation on tunnel face. As conventional methods, the inter-frame difference method and the laser measurement method were proposed. However, those methods were difficult to monitor the entire tunnel face and detected moving objects other than falling rocks. In this paper, we propose a falling rocks detection method that combines the moving object detection method on the tunnel face and the estimation method of excavation points using single color markers. It was confirmed that only falling rocks were detected during excavation experiment. © 2022, Society for Imaging Science and Technology.

关键词： industrial hygiene

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3D Joist Perception, Detection, and Climbing for Hexapod Robot

3D Joist Perception, Detection, and Climbing for Hexapod Rob...

引用

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

作者： Li, Yibin Zakhor, Avideh Department of Electrical Engineering and Computer Science University of California Berkeley United States

Avoiding obstacles is challenging for autonomous robotic systems. In this work, we examine obstacle avoidance for legged hexapods, as it relates to climbing over randomly placed wooden joists. Our main motivation is to enable robots to navigate inside tight attic spaces of single-family residential homes in the U.S., which typically contain rows of 4, 6, or 8 inch tall joists placed 16 inches apart from each other. We formulate the task as a 3D joist detection problem, and propose a detect-plan-act pipeline using a simultaneous localization and mapping (SLAM) algorithm to generate a pointcloud and a grid map to expose high obstacles such as joists. A line detector is applied on the grid map to extract parameters of the joist, such as height, orientation, and distance;based on this information the hexapod plans a sequence of leg movements to either climb over the joist or move sideways if the joist is too high. We show that our perception and path planning modules work well on the real-world joists with different heights and orientations. © 2023, Society for Imaging Science and Technology.

关键词： Motion planning

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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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using shape descriptors for uav detection

Using shape descriptors for uav detection

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intelligent robotics and industrial applications using computer vision 2018, iriacv 2018

作者： Unlu, Eren Zenou, Emmanuel Riviere, Nicolas ISAE-SUPAERO Toulouse France ONERA Toulouse France

The rapid development of Unmanned Aerial Vehicle (UAV) technology, -also known as drones- has raised concerns on the safety of critical locations such as governmental buildings, nuclear stations, crowded places etc. computer vision based approach for detecting these threats seems as a viable solution due to various advantages. We envision an autonomous drone detection and tracking system for the protection of strategic locations. It has been reported numerous times that, one of the main challenges for aerial object recognition with computer vision is discriminating birds from the targets. In this work, we have used 2-dimensional scale, rotation and translation invariant Generic Fourier Descriptor (GFD) features and classified targets as a drone or bird by a neural network. For the training of this system, a large dataset composed of birds and drones is gathered from open sources. We have achieved up to 85.3% overall correct classification rate. © 2018, Society for Imaging Science and Technology.

关键词： Drones

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