An Outdoor Stereo Vision Brick Recognition System for Construction Robots

1996 ◽  
Author(s):  
L. A. Slivovsky ◽  
K. Rahardja ◽  
J. Edwards ◽  
A. Kak ◽  
Y. Tanaka
Keyword(s):  
Stereo Vision ◽  
Recognition System

Symbol recognition system based on 3D stereo vision

2020 ◽  
pp. 1-10
Author(s):  
Linlin Wang
Keyword(s):  
Camera Calibration ◽  
Stereo Vision ◽  
Stereo Matching ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Recognition System ◽  
Symbol Recognition ◽  
Two Dimensional ◽  
Measuring Machine ◽  
Left And Right

With the continuous development of computer science and technology, symbol recognition systems may be converted from two-dimensional space to three-dimensional space. Therefore, this article mainly introduces the symbol recognition system based on 3D stereo vision. The three-dimensional image is taken by the visual coordinate measuring machine in two places on the left and right. Perform binocular stereo matching on the edge of the feature points of the two images. A corner detection algorithm combining SUSAN and Harris is used to detect the left and right camera calibration templates. The two-dimensional coordinate points of the object are determined by the image stereo matching module, and the three-dimensional discrete coordinate points of the object space can be obtained according to the transformation relationship between the image coordinates and the actual object coordinates. Then draw the three-dimensional model of the object through the three-dimensional drawing software. Experimental data shows that the logic resources and memory resources occupied by image preprocessing account for 30.4% and 27.4% of the entire system, respectively. The results show that the system can calibrate the internal and external parameters of the camera. In this way, the camera calibration result will be more accurate and the range will be wider. At the same time, it can effectively make up for the shortcomings of traditional modeling techniques to ensure the measurement accuracy of the detection system.

scholarly journals INITIAL EVALUATION OF THE POTENTIAL OF SMARTPHONE STEREO-VISION IN MUSEUM VISITS

2019 ◽  
Vol XLII-2/W11 ◽  
pp. 837-842
Author(s):  
A. Masiero ◽  
G. Tucci ◽  
A. Conti ◽  
L. Fiorini ◽  
A. Vettore
Keyword(s):  
Augmented Reality ◽  
Stereo Vision ◽  
3D Model ◽  
New Technologies ◽  
Recognition System ◽  
Neural Network Classifier ◽  
Visual Effects ◽  
Geometric Information ◽  
Traditional Use ◽  
Museum Visit

<p><strong>Abstract.</strong> The recent introduction of new technologies such as augmented reality, machine learning and the worldwide spread of mobile devices provided with imaging, navigation sensors and high computational power can be exploited in order to drammatically change the museum visit experience. Differently from the traditional use of museum docents or audio guides, the introduction of digital technologies already proved to be useful in order to improve the interest of the visitor thanks to the increased interaction and involvement, reached also by means of visual effects and animations. Actually, the availability of 3D representations, augmented reality and navigation abilities directly on the visitor’s device can lead to a personalized visit, enabling the visitor to have an experience tailored on his/her needs. In this framework, this paper aims at investigating the potentialities of smartphone stereo-vision to improve the geometric information about the artworks available on the visitor’s device. More specifically, in this work smartphone stereo-vision will used as a 3D model generation tool in a 3D artwork recognition system based on a neural network classifier.</p>

scholarly journals Online Training for Face Recognition System Using Improved PCA

2011 ◽  
Vol 2 (2) ◽  
pp. 1303
Author(s):  
Widodo Budiharto
Keyword(s):  
Face Recognition ◽  
Stereo Vision ◽  
Indoor Environment ◽  
Online Training ◽  
Recognition System ◽  
Service Robot ◽  
Challenging Problem ◽  
Face Database ◽  
Face Images ◽  
Face Recognition System

The variation in illumination is one of the main challenging problem for face recognition. It has been proven that in face recognition, differences caused by illumination variations are more significant than differences between individuals. Recognizing face reliably across changes in pose and illumination using PCA has proved to be a much harder problem because eigenfaces method comparing the intensity of the pixel. To solve this problem, this research proposes an online face recognition system using improved PCA for a service robot in indoor environment based on stereo vision. Tested images are improved by generating random values for varying the intensity of face images. A program for online training is also developed where the tested images are captured real-time from camera. Varying illumination in tested images will increase the accuracy using ITS face database which its accuracy is 95.5 %, higher than ATT face database’s as 95.4% and Indian face database’s as 72%. The results from this experiment are still evaluated to be improved in the future.

scholarly journals Development & Evaluation of a Surgical Stereo Vision Laser-Scanning Surface Recognition System

2013 ◽  
Author(s):  
Pascal Wettmann ◽  
Florian Coigny ◽  
Gregor Imboden ◽  
Bruno Knobel ◽  
Erik Schkommodau
Keyword(s):  
Stereo Vision ◽  
Laser Scanning ◽  
Recognition System ◽  
Surface Recognition ◽  
Development Evaluation

A gesture recognition system using stereo vision and arm model fitting

2007 ◽  
Vol 1301 ◽  
pp. 89-92 ◽  
Author(s):  
Masaki Shimizu ◽  
Takeharu Yoshizuka ◽  
Hiroyuki Miyamoto
Keyword(s):  
Gesture Recognition ◽  
Stereo Vision ◽  
Model Fitting ◽  
Recognition System

Face Recognition Based on Symmetrical Half-Join Method using Stereo Vision Camera

2016 ◽  
Vol 6 (6) ◽  
pp. 2818 ◽  
Author(s):  
Edy Winarno ◽  
Agus Harjoko ◽  
Aniati Murni Arymurthy ◽  
Edi Winarko
Keyword(s):  
Face Recognition ◽  
Stereo Vision ◽  
Recognition Rate ◽  
Recognition System ◽  
Face Images ◽  
Face Recognition System ◽  
Proposed Model ◽  
The Face ◽  
Left And Right ◽  
Recognition Technique

<p>The main problem in face recognition system based on half-face pattern is how to anticipate poses and illuminance variations to improve recognition rate. To solve this problem, we can use two lenses on stereo vision camera in face recognition system. Stereo vision camera has left and right lenses that can be used to produce a 2D image of each lens. Stereo vision camera in face recognition has capability to produce two of 2D face images with a different angle. Both angle of the face image will produce a detailed image of the face and better lighting levels on each of the left and right lenses. In this study, we proposed a face recognition technique, using 2 lens on a stereo vision camera namely symmetrical half-join. Symmetrical half-join is a method of normalizing the image of the face detection on each of the left and right lenses in stereo vision camera, then cropping and merging at each image. Tests on face recognition rate based on the variety of poses and variations in illumination shows that the symmetrical half-join method is able to provide a high accuracy of face recognition and can anticipate variations in given pose and illumination variations. The proposed model is able to produce 86% -97% recognition rate on a variety of poses and variations in angles between 0 °- 22.5 °. The variation of illuminance measured using a lux meter can result in 90% -100% recognition rate for the category of at least dim lighting levels (above 10 lux).</p>

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