computer vision techniques for underwater navigation

Computer Vision Techniques for Underwater Navigation

Chris BarngroverCSE 291 May 5, 2010

Doppler Velocity Logger

SONAR

Cameras

AUVSI & ONR’s 13th Annual AUV Competition

Specific MotivationSpecific Motivation

TRANSDEC

Detect and Classify Objects

◦ Buoy

◦ Pipe

Research GoalResearch Goal

The StingrayThe StingrayCameras

FrameGrabber

Processor

Labeling Examples

Computer VisionComputer Vision

HSV Classifier◦ Hue – Saturation – Value◦ RGB is lighting dependant

Computer VisionComputer Vision

Boosting Algorithms◦ JBoost

Computer VisionComputer Vision

Binary Image

Computer VisionComputer Vision

Computer VisionComputer Vision

Detect & Classify Determine Center Location

Buoy DetectionBuoy Detection

Baseline Algorithm◦ HSV Range◦ Misses Reflection◦ Noise

Buoy DetectionBuoy Detection

Boosting Benefits◦ HSV Classifier◦ Robust Scoring per pixel◦ Reduced Noise

Buoy DetectionBuoy Detection

Opening◦ Reduces Noise◦ Erosion then Dilation

Buoy DetectionBuoy Detection

Closing◦ Fills holes◦ Dilation then Erosion

Buoy DetectionBuoy Detection

Convex Hull◦ Closes edges

Buoy DetectionBuoy Detection

Center Estimation◦ Centroids of Blobs◦ Largest Area Wins◦ Quality of Classifier

Buoy DetectionBuoy Detection

Hybrid Boosting◦ TRANSDEC & Pool◦ Separate Decision Trees◦ Additive Scoring

Buoy DetectionBuoy Detection

Reflection Problem◦ Larger Reflection Blob◦ Look at 2nd Largest

Buoy DetectionBuoy Detection

Buoy DetectionBuoy DetectionBaseline Metrics

Final Algorithm Metrics

Detect & Classify Determine Center Location Determine Bearing

Pipe DetectionPipe Detection

Baseline Algorithm◦ HSV Range◦ Finds Pipe Generally◦ Lots of Noise

Pipe DetectionPipe Detection

Boosting◦ HSV Classifier

Post Processing◦ Opening◦ Closing◦ Convex Hull◦ Smooth

Pipe DetectionPipe Detection

Edge Detection◦ Blob Perimeter◦ Canny Algorithm

Pipe DetectionPipe Detection

Hough Transform◦ Standard (SHT)◦ Probabilistic (PHT)◦ Multiple lines per edge

Pipe DetectionPipe Detection

Collinear Lines◦ Merge semi-collinear◦ Error from best-fit

Pipe DetectionPipe Detection

Parallel Lines◦ Remove solo lines

Pipe DetectionPipe Detection

Two Pipes◦ Match lines with center

of pipe

Pipe DetectionPipe Detection

Two Line Pairs◦ Choose pair closest

to the center

Pipe DetectionPipe Detection

Pipe DetectionPipe DetectionBaseline Metrics

Final Algorithm Metrics

Fish Detection

Quagga Mussels

Mine Detection

Future EffortsFuture Efforts

Perceptual Robotics Laboratory @ UMich◦ Visually Augmented Navigation◦ Autonomous Ship Hull Inspection

Koch Lab @ Cal Tech◦ Automated Event Detection in Underwater Video

Singh’s Lab @ Woods Hole◦ Underwater Photo Mosaicing

Related WorkRelated Work

Questions?Questions?