Design and Implementation of Vehicle Safety Robot Based on Computer Vision

Author(s):  
Yuankai Ma ◽  
Xubo Liu ◽  
Jiahang Bao ◽  
Chang Liu ◽  
Zhitao Dai
2021 ◽  
Author(s):  
Abhi Lad ◽  
Prithviraj Kanaujia ◽  
Soumya ◽  
Yash Solanki

2007 ◽  
Vol 8 (1) ◽  
pp. 108-120 ◽  
Author(s):  
Mohan Manubhai Trivedi ◽  
Tarak Gandhi ◽  
Joel McCall

1995 ◽  
Vol 32 (3) ◽  
pp. 235-255
Author(s):  
T. David Binnie ◽  
I. Reading

Image capture board for the PC We report the design and implementation of a low cost, image capture board for an IBM type personal computer. The board is particularly suited to computer vision education. The board provides: image capture at video rate, random access to xy addressable image data, and options for on-board image processing hardware.


2014 ◽  
Vol 26 (02) ◽  
pp. 1450018 ◽  
Author(s):  
Carlos Perez-Vidal ◽  
Alejandro Garcia ◽  
Nicolas Garcia-Aracil ◽  
Jose M. Sabater ◽  
Eduardo Fernandez

The aim of the work presented in this paper is the design, manufacturing and assembling of a system able to measure rodents' (mice and rats) visual function and to study the evolution of degenerative retina diseases. Measurement of contrast sensitivity and visual acuity is essential to design new drugs and understand mechanisms of visual development to evaluate treatments' effectiveness. Classical methods to study visual perception of animals such as electroretinogram (ERG) or histological analysis are not supplying enough information because connection between eyes and brain is not considered. The system proposed in this work consists of four screens forming a cube with black methacrylate plastic floor and roof. Screens display visual stimulus and the rodent's behaviour (placed over a platform in the middle of the cube) is analized to determine its visual acuity and contrast sensitivity. These visual stimuli are generated from a FPGA board designed in this project. This board has a USB link with a computer and it controls screens via VGA signals. Rodents' behaviour is analized using computer vision algorithms under OpenCV libraries. To test the system, more than 30 mice (C57 and RD10 type) have been used to validate the hardware, the software, the procedure and protocol.


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