Stereoscopic Imaging for Slow-Moving Autonomous Vehicle

Senior Project ProposalBradley 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

CamerasLaptopSoftware

Mode of operationCalibration modeRun mode

System Block Diagram

Cameras Subsystem

Laptop Subsystem

Laptop

Camera 1 Image

Camera 2 Image

User Input

Camera 1 Image capture signal

Movement instructions

Display 3D map on screen

Camera 2 Image capture signal

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

Disparity Map Formed Using Left and Right Images

Represents the differences in corresponding pixels between the left and right cameras

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?