visual odometry for vehicles in urban environments cs223b computer vision, winter 2008 team 3: david...
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Visual Odometry for Vehicles in Urban Environments
CS223B Computer Vision, Winter 2008Team 3: David Hopkins, Christine Paulson, Justin Schauer
Goal: Determine Vehicle Trajectory from Video Cameras Mounted on a Vehicle
• 2 calibrated cameras: forward-looking & side-looking with non-overlapping field of view
• Compare visual odometry results to GPS and inertial sensor ground-truth data
Approach: SIFT features, RANSAC, derive rotation and translation from essential matrix
1. Identify corresponding SIFT features between image pairs2. Estimate the fundamental matrix that satisfies the epipolar
constraint for uncalibrated cameras: using adaptive RANSAC to refine F and reject outliers3. Compute the essential matrix from the fundamental matrix
and the camera calibration matrix: 4. Recover rotation and translation components from the
essential matrix using singular value decomposition (SVD)
4 solutions:Pick one where world points are in front of both cameras
Selecting reliable features is key3067 SIFT candidate features
276 feature correspondences after mutual consistency check
69 feature correspondences after RANSAC
Example Trajectory Animation
Car turns left, then right onto a street with oncoming traffic
Mean Absolute Error: 6 mTotal Distance: 322 m
Link 2 3
Web 2 3
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are needed to see this picture.
Mean Absolute Error: 1 – 3 percent
Car driving backwards
Mean Absolute Error: 2.2 mTotal Distance: 141 m
Straight road with lots of traffic
Mean Absolute Error: 2.7m Total Distance: 312 m
Mean Absolute Error: 0.3 m Total Distance: 27 m
Mean Absolute Error: 0.6 m Total Distance: 23 m
Mean Absolute Error: 1.7 m Total Distance: 90 m
Conclusions / Issues
• Cumulative error is extremely sensitive to orientation
• Adaptive RANSAC was helpful in reducing effects of moving vehicles
• Visual odometry is not a replacement for GPS, but could be used as an alternate or complementary method to GPS (i.e. tunnels, parking structures, Mars rovers)