Low-Cost Real-Time Stereo Vision Hardware with Binary Confidence Metric and Disparity Refinement

2011 ◽  
Vol 1 (2) ◽  
pp. 70-77
Author(s):  
Andy Motten ◽  
Luc Claesen
Keyword(s):  
2012 ◽  
Vol 36 (4) ◽  
pp. 281-288 ◽  
Author(s):  
Paolo Zicari ◽  
Stefania Perri ◽  
Pasquale Corsonello ◽  
Giuseppe Cocorullo

2017 ◽  
Vol 2017 (9) ◽  
pp. 10-15 ◽  
Author(s):  
Soonhac Hong ◽  
Ming Li ◽  
Miao Liao ◽  
Peter van Beek

2014 ◽  
Vol 619 ◽  
pp. 249-253
Author(s):  
Viboon Sangveraphunsiri ◽  
Pongsakon Bamrungthai

In this paper, a 3-D pose estimation system by using stereo vision with low-cost devices is presented. It is developed as a base system for application development. Two webcams and a planar target with circular markers are used to reduce development cost and computational complexity. To avoid correspondence search problem, user has to select regions of interest (ROI’s) of each marker on the two images in the same sequence before starting the 3-D reconstruction process. Linear triangulation method is applied for 3-D position calculation of each marker. These positions and the positions of the markers referenced in the planar target coordinate frame are used for pose estimation by using least-squares fitting algorithm to obtain the position and orientation of the planar target. The system can be applied for robot tracking as shown in the experiments. The experimental results validate the system’s ability to estimate object pose in real-time with minimum system frequency of 25 Hz.


Author(s):  
Ildar Rakhmatulin ◽  
Eugene Pomazov

The paper presents an analysis of the latest developments in the field of stereo vision in the low-cost segment, both for prototypes and for industrial designs. We described the theory of stereo vision and presented information about cameras and data transfer protocols and their compatibility with various devices. The theory in the field of image processing for stereo vision processes is considered and the calibration process is described in detail. Ultimately, we presented the developed stereo vision system and provided the main points that need to be considered when developing such systems. The final, we presented software for adjusting stereo vision parameters in real-time in the python language in the Windows operating system.


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