- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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[IEEE 2018 4th International Conference on Frontiers of Signal Processing (ICFSP) - Poitiers, France (2018.9.24-2018.9.27)] 2018 4th International Conference on Frontiers of Signal Processing (ICFSP) - Improvement of the System for Measuring VDT Working Hours Using a Webcam
摘要： This paper presents an improvement method for enhancing performance of a system for measuring VDT working hours using a webcam. This system is utilized in companies to avoid long VDT work. Assuming large-volume introduction of the system into companies, the system monitors the PC user using images obtained by a common webcam considering cost performance. However, the system can hardly measure the time, i.e., cannot recognize existence of the PC user in the cases when a user wears glasses or masks. This monitoring differs from regular face recognition and it is not easy to recognize existence of a user who works in front of a monitor because users do not always face to the camera. In this research, a method for recognizing glasses and a mask in YCbCr color space has been introduced into the existing system. From experimental results that accuracy ratios for recognizing existence of a user who wears one of the items were more than 80% to 9 of 10 participants and very similar to accuracy in the existing system for users who do not wear them, we confirmed the improvement is effective enough in the system.
关键词： image recognition,computer vision syndrome,image processing,visual display terminal
更新于2025-09-09 09:28:46
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Non-contact fatigue crack detection in civil infrastructure through image overlapping and crack breathing sensing
摘要： Fatigue cracks are of critical structural safety concern in civil infrastructure. Many existing fatigue crack sensing methods are contact-based, hence extensive human operation is necessary for sensor and/or actuator deployment. In this study, we propose a vision-based non-contact approach to detect fatigue cracks through image overlapping. We treat crack breathing behavior, the small cyclic movement of the crack perpendicular to the crack path under repetitive fatigue loads, as a robust indicator for crack identification. The differential image features provoked by a breathing crack can be extracted, enhanced, and visualized through a series of image processing techniques. The performance of the proposed approach is experimentally validated through two laboratory setups including a small-scale steel compact specimen and a large-scale bridge to cross-frame connection specimen. Test results demonstrate the capability of the proposed approach in reliably identifying the fatigue crack, even the true crack is surrounded by other non-crack features.
关键词： Computer vision,Bridges,Civil infrastructure,Feature matching,Non-contact sensing,Image processing,Structural health monitoring,Image registration,Breathing crack,Fatigue crack detection
更新于2025-09-04 15:30:14
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[IEEE 2018 24th International Conference on Pattern Recognition (ICPR) - Beijing, China (2018.8.20-2018.8.24)] 2018 24th International Conference on Pattern Recognition (ICPR) - A Fast Local Analysis by Thresholding applied to image matching
摘要： Keystructures extraction and matching are key steps in computer vision. Many fields of application need large image acquisition and fast extraction of finest structures. In this study, we focus on situations where existing local feature extractors give not enough satisfying results concerning both accuracy and time processing. Among good illustrations, we can quote short-line extraction in local weakly-contrasted images. We propose a new Fast Local Analysis by threSHolding (FLASH) designed to process large images under hard time constraints. We use "micro-line" points as key feature. These are used for shape reconstruction (like lines) and local signature design. We apply FLASH on the field of concrete infrastructure monitoring where robots and UAVs are more and more used for automated defect detection (like cracks). For large concrete surfaces, there are several hard constraints such as the computational time and the reliability. Results show us that the computations are faster than several existing algorithms in image matching and FLASH has invariance to rotation, partial occlusion, and scale range from 0.7 to 1.4 without scale-space exploration.
关键词： concrete infrastructure monitoring,crack detection,computer vision,feature extraction,FLASH,image matching
更新于2025-09-04 15:30:14
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Ensuring the Accuracy of Traffic Monitoring Using Unmanned Aerial Vehicles Vision Systems
摘要： The paper is dedicated to the organization of traffic monitoring using unmanned aerial vehicles (UAV). It is demonstrated that the monitoring of traffic makes high demands on the accuracy of determining the position of the vehicle on the road. It is assumed that the purpose of monitoring is detecting specific situations, which may include accident, in particular, car collision; traffic accidents, reducing the bandwidth of the road section; movement of the vehicle, being a threat to other road users. Detection of such situations requires assessment of the following at the received images: ? Vehicles position relatively to the road markings; ? Vehicles position relatively to each other; ? Vehicles speed. Review of the literature showed that the existing tools for tracking ground objects movements provide sufficiently accurate assessment of the vehicles coordinates at the images. Thus, an important issue is the estimation of vehicle position with respect to the road, i.e. in the ground coordinate system of the road. Different options of the vehicle position assessment relatively the road are researched. Evaluation of the content and accuracy of the standard UAV navigation system showed that the option of monitoring based on the use of UAV position assessment relative to the ground coordinate system and the vehicles is non-implementable because of lack of precision at the standard navigation system, including, corrected using the satellite navigation system. Assessing the position of the vehicle relative to the roadside is proposed to be made using image processing algorithms, particularly the contour lines highlighting and the Hough algorithm for straight segments highlighting. The research shows that this option based on direct assessment of the situation with respect to the vehicle position on the road image is physically implementable.
关键词： computer vision system,Unmanned Aerial Vehicles (UAV),vehicles monitoring,image processing,road segments allocation
更新于2025-09-04 15:30:14
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[IEEE 2018 International Conference on Current Trends towards Converging Technologies (ICCTCT) - Coimbatore, India (2018.3.1-2018.3.3)] 2018 International Conference on Current Trends towards Converging Technologies (ICCTCT) - Processing Retinal Images to Discover Diseases
摘要： The retina of a human eye consists of billion of photosensitive cells (rods and cones) and alternative nerve cells that acquire and arrange visual information. The retina of a human eye is a thin tissue layer on the inside back wall of your eye. Three of the are Diabetic retinal diseases most Retinopathy, Glaucoma, and Cataract. The world is presently experiencing an epidemic of Diabetic Retinopathy (DR). Current predictions draw an estimation of doubling of the number affected from the current 170 million to an estimated 367 million by 2030. We propose a system wherein we extract blood vessels of the retina to detect eye diseases. Manually extracting the blood vessels of the human retina is a time-consuming task, and thus an automation of this process results in easy implementation of the work. This paper aims to design and consequently implement deep convolutional neural networks to identify the presence of an exudate, and thereby classify it into Diabetic Retinopathy, Glaucoma, and/or Cataract.
关键词： Computer vision,Glaucoma,Diabetic Retinopathy,Cataract,Convolutional Neural Networks,Retinal disease detection,CNN
更新于2025-09-04 15:30:14
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Distinguishing Refracted Features using Light Field Cameras with Application to Structure from Motion
摘要： To be effective, robots will need to reliably operate in scenes with refractive objects in a variety of applications; however, refractive objects can cause many robotic vision algorithms, such as structure from motion, to become unreliable or even fail. We propose a novel method to distinguish between refracted and Lambertian image features using a light field camera. While previous refracted feature detection methods are limited to light field cameras with large baselines relative to the refractive object, our method achieves comparable performance, and we extend these capabilities to light field cameras with much smaller baselines than previously considered, where we achieve up to 50% higher refracted feature detection rates. Specifically, we propose to use textural cross correlation to characterize apparent feature motion in a single light field, and compare this motion to its Lambertian equivalent based on 4-D light field geometry. For structure from motion, we demonstrate that rejecting refracted features using our distinguisher yields lower reprojection error, lower failure rates, and more accurate pose estimates when the robot is approaching refractive objects. Our method is a critical step toward allowing robots to operate in the presence of refractive objects.
关键词： Computer vision for automation,light fields,computational imaging,visual-based navigation
更新于2025-09-04 15:30:14
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Real-time car tracking system based on surveillance videos
摘要： As a variety of video surveillance devices such as CCTV, drones, and car dashboard cameras have become popular, numerous studies have been conducted regarding the effective enforcement of security and surveillance based on video analysis. In particular, in car-related surveillance, car tracking is the most challenging task. One early approach to accomplish such a task was to analyze frames from different video sources separately. Considering the shooting range of the bulk of video devices, the outcome from the analysis of single video source is highly limited. To obtain more comprehensive information for car tacking, a set of video sources should be considered together and the relevant information should be integrated according to spatial and temporal constraints. Therefore, in this study, we propose a real-time car tracking system based on surveillance videos from diverse devices including CCTV, dashboard cameras, and drones. For scalability and fault tolerance, our system is built on a distributed processing framework and comprises a Frame Distributor, a Feature Extractor, and an Information Manager. The Frame Distributor is responsible for distributing the video frames from various devices to the processing nodes. The Feature Extractor extracts principal vehicle features such as plate number, location, and time from each frame. The Information Manager stores all the features into a database and handles user requests by collecting relevant information from the feature database. To illustrate the effectiveness of our proposed system, we implemented a prototype system and performed a number of experiments. We report some of the results.
关键词： Computer vision,Automobile tracking system,Real-time,Index structure,Database
更新于2025-09-04 15:30:14
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[Studies in Computational Intelligence] Recent Advances in Computer Vision Volume 804 (Theories and Applications) || Analysis and Evaluation of Keypoint Descriptors for Image Matching
摘要： Feature keypoint descriptors have become indispensable tools and have been widely utilized in a large number of computer vision applications. Many descriptors have been proposed in the literature to describe regions of interest around each keypoint and each claims distinctiveness and robustness against certain types of image distortions. Among these are the conventional ?oating-point descriptors and their binary competitors that require less storage capacity and perform at a fraction of the matching times compared with the ?oating-point descriptors. This chapter gives a brief description to the most frequently used keypoint descriptors from each category. Also, it provides a general framework to analyze and evaluate the performance of these feature keypoint descriptors, particularly when they are used for image matching under various imaging distortions such as blur, scale and illumination changes, and image rotations. Moreover, it presents a detailed explanation and analysis of the experimental results and ?ndings where several important observations are derived from the conducted experiments.
关键词： image matching,keypoint descriptors,binary descriptors,computer vision,floating-point descriptors
更新于2025-09-04 15:30:14