VCS-IV: A real-time vision system using a digital vision chip

2006 ◽  
Vol 89 (6) ◽  
pp. 34-43 ◽  
Author(s):  
Shingo Kagami ◽  
Takashi Komuro ◽  
Yoshihiro Watanabe ◽  
Masatoshi Ishikawa
Keyword(s):  
Real Time ◽  
Vision System ◽  
Vision Chip

scholarly journals Multi-Target Tracking Using a Vision Chip and its Applications to Real-Time Visual Measurement

2005 ◽  
Vol 17 (2) ◽  
pp. 121-129 ◽  
Author(s):  
Yoshihiro Watanabe ◽  
◽  
Takashi Komuro ◽  
Shingo Kagami ◽  
Masatoshi Ishikawa
Keyword(s):  
Image Processing ◽  
Target Tracking ◽  
Real Time ◽  
High Speed ◽  
Vision System ◽  
Visual Observation ◽  
Frame Rate ◽  
Vision Chip ◽  
Visual Measurement ◽  
Multi Target Tracking

Real-time image processing at high frame rates could play an important role in various visual measurement. Such image processing can be realized by using a high-speed vision system imaging at high frame rates and having appropriate algorithms processed at high speed. We introduce a vision chip for high-speed vision and propose a multi-target tracking algorithm for the vision chip utilizing the unique features. We describe two visual measurement applications, target counting and rotation measurement. Both measurements enable excellent measurement precision and high flexibility because of high-frame-rate visual observation achievable. Experimental results show the advantages of vision chips compared with conventional visual systems.

scholarly journals Data integration by two-sensors in a LEAP-based Virtual Glove for human-system interaction

2021 ◽  
Author(s):  
Giuseppe Placidi ◽  
Danilo Avola ◽  
Luigi Cinque ◽  
Matteo Polsinelli ◽  
Eleni Theodoridou ◽  
...  
Keyword(s):  
Data Integration ◽  
Real Time ◽  
Vision System ◽  
Hand Tracking ◽  
Selection Strategy ◽  
Motion Sensors ◽  
Leap Motion ◽  
Time Data ◽  
Lower Velocity ◽  
Human System

AbstractVirtual Glove (VG) is a low-cost computer vision system that utilizes two orthogonal LEAP motion sensors to provide detailed 4D hand tracking in real–time. VG can find many applications in the field of human-system interaction, such as remote control of machines or tele-rehabilitation. An innovative and efficient data-integration strategy, based on the velocity calculation, for selecting data from one of the LEAPs at each time, is proposed for VG. The position of each joint of the hand model, when obscured to a LEAP, is guessed and tends to flicker. Since VG uses two LEAP sensors, two spatial representations are available each moment for each joint: the method consists of the selection of the one with the lower velocity at each time instant. Choosing the smoother trajectory leads to VG stabilization and precision optimization, reduces occlusions (parts of the hand or handling objects obscuring other hand parts) and/or, when both sensors are seeing the same joint, reduces the number of outliers produced by hardware instabilities. The strategy is experimentally evaluated, in terms of reduction of outliers with respect to a previously used data selection strategy on VG, and results are reported and discussed. In the future, an objective test set has to be imagined, designed, and realized, also with the help of an external precise positioning equipment, to allow also quantitative and objective evaluation of the gain in precision and, maybe, of the intrinsic limitations of the proposed strategy. Moreover, advanced Artificial Intelligence-based (AI-based) real-time data integration strategies, specific for VG, will be designed and tested on the resulting dataset.

scholarly journals A real-time machine-vision system for monitoring the textile raising process

2005 ◽  
Vol 56 (8-9) ◽  
pp. 831-842 ◽  
Author(s):  
Monica Carfagni ◽  
Rocco Furferi ◽  
Lapo Governi
Keyword(s):  
Machine Vision ◽  
Real Time ◽  
Vision System ◽  
Machine Vision System ◽  
Time Machine

Real-time Wearable Computer Vision System for Improved Museum Experience

2016 ◽  
Author(s):  
Giovanni Taverriti ◽  
Stefano Lombini ◽  
Lorenzo Seidenari ◽  
Marco Bertini ◽  
Alberto Del Bimbo
Keyword(s):  
Computer Vision ◽  
Real Time ◽  
Vision System ◽  
Wearable Computer ◽  
Computer Vision System ◽  
Museum Experience

Development of a real-time machine vision system for functional textile fabric defect detection using a deep YOLOv4 model

2021 ◽  
pp. 004051752110342
Author(s):  
Sifundvolesihle Dlamini ◽  
Chih-Yuan Kao ◽  
Shun-Lian Su ◽  
Chung-Feng Jeffrey Kuo
Keyword(s):  
Machine Vision ◽  
Real Time ◽  
Defect Detection ◽  
Data Augmentation ◽  
Detection System ◽  
Vision System ◽  
Good Precision ◽  
Machine Vision System ◽  
Time Machine ◽  
Textile Fabric

We introduce a real-time machine vision system we developed with the aim of detecting defects in functional textile fabrics with good precision at relatively fast detection speeds to assist in textile industry quality control. The system consists of image acquisition hardware and image processing software. The software we developed uses data preprocessing techniques to break down raw images to smaller suitable sizes. Filtering is employed to denoise and enhance some features. To generalize and multiply the data to create robustness, we use data augmentation, which is followed by labeling where the defects in the images are labeled and tagged. Lastly, we utilize YOLOv4 for localization where the system is trained with weights of a pretrained model. Our software is deployed with the hardware that we designed to implement the detection system. The designed system shows strong performance in defect detection with precision of [Formula: see text], and recall and [Formula: see text] scores of [Formula: see text] and [Formula: see text], respectively. The detection speed is relatively fast at [Formula: see text] fps with a prediction speed of [Formula: see text] ms. Our system can automatically locate functional textile fabric defects with high confidence in real time.

Development of a real-time computer vision system for tracking loose-housed pigs

2011 ◽  
Vol 76 (2) ◽  
pp. 169-174 ◽  
Author(s):  
Peter Ahrendt ◽  
Torben Gregersen ◽  
Henrik Karstoft
Keyword(s):  
Computer Vision ◽  
Real Time ◽  
Vision System ◽  
Computer Vision System
Sign in / Sign up

Export Citation Format

Share Document