By: Alex Norton Advisor: Dr. Huggins November 15, 2011

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Presentation transcript:

By: Alex Norton Advisor: Dr. Huggins November 15, 2011 Stereoscopic Imaging for Slow-Moving Autonomous Vehicle Senior Project Proposal Bradley University ECE Department By: Alex Norton Advisor: Dr. Huggins November 15, 2011

Presentation Outline Introduction to stereoscopic imaging Project goals Previous work Project description Preliminary lab work Equipment list Schedule of tasks for spring

What is Stereoscopic Imaging? The use of two horizontally aligned, slightly offset cameras taking a pair of images at the same time By matching corresponding pixels between the two images, the distances to objects can be calculated using triangulation This depth information can be used to create a 3-D image and terrain map

Project Goals Learn theory of 3D stereoscopic imaging Investigate existing software (OpenCV and MATLAB) Control cameras Calibrate cameras Take and store images Process images for objects Correlate objects Compute distance to objects Compute terrain map

Previous Work BirdTrak (Brian Crombie and Matt Zivney, 2003) Bradley Rover(Steve Goggins, Rob Scherbinski, Pete Lange, 2005) NavBot (Adam Beach, Nick Wlaznik, 2007) SVAN (John Hessling, 2010)

Project Description System block diagram Subsystem block diagrams Cameras Laptop Software Mode of operation Calibration mode Run mode

System Block Diagram

Cameras Subsystem

Laptop Subsystem

Software

Calibration Mode Initial mode of operation Ensures the accuracy of the terrain map generated in run mode by correcting for lens distortion Cameras will take images of a chessboard in multiple orientations Camera intrinsic and distortion parameters can be determined, which are used to correct for distortion in images from un-calibrated cameras

Run Mode Primary mode of operation entered once cameras are calibrated Cameras capture a set of images after receiving signals from the laptop A disparity map is created using the two images and distances to objects are calculated This information is used to generate a terrain map which is stored in a text file to be used to navigate an autonomous vehicle

Preliminary Lab Work Current test camera setup

Preliminary Lab Work Left Camera image Right Camera Image

Preliminary Lab Work Edge Detection of Left Image Edge Detection of Right Image

Preliminary Lab Work Represents the differences in corresponding pixels between the left and right cameras Disparity Map Formed Using Left and Right Images

Equipment List Two Logitech Quickcam Express webcams Compaq Presario CQ60 laptop Mathworks Matlab Microsoft Visual Studio 2008 OpenCV Equipment to be ordered: Two webcams compatible with Windows 7 and Linux

Preliminary Lab Work MATLAB code that sets up the webcams to receive image data from them

Preliminary Lab Work MATLAB code that gets an image from each camera, filters them using the median filter function, uses the canny edge detection function, and displays the filtered images and edge detected images

Schedule of Spring Tasks

Questions?