Street Crossing

1
Street Crossing

• Tracking from a moving platform
• Need to look left and right to find a safe time
  to cross
• Need to look ahead to drive to other side of road
• Must stay in crosswalk

2
Algorithm for Tracking Cars

• Use image differencing method to extract motion
  regions
• Noise filter using 3x3 median filter effective
  for typical CCD sensor noise
• Compute edges of motion regions using Canny edge
  detection
• Use Moris sign pattern to find bottoms of cars
  Mori 1994
• Find bounding boxes of moving objects
• Use knowledge from prior frames to mark direction
  of travel of each bounding box

3
Mori Sign Pattern

• Tracking algorithm uses Mori Scan to reliably
  detect undersides of cars
• The Mori sign pattern for vehicle detection
  says the shadow underneath a vehicle is darker
  than any other spot on the paved road
• The Mori result is invariant to lighting and
  holds for wet and dry roads
• Use of the Mori result obviates the need for
  explicit shadow detection and/or removal
  previously, prominent shadow edges caused
  oversize bounding boxes

4
Mori Sign Pattern
5
Mori Sign Pattern
6
Street Crossing

• Six frames of a tracking sequence

7
System Validation

• When it is safe to cross, a person monitoring the
  traffic
• scene presses a button
• A second button press means it is no longer safe
  to cross
• The time between button presses specifies a safe
  crossing window
• Use more than one person to compensate for
  individual risk tolerance
• Button press data is synchronized with the video
  data
• Compare system safety estimates to human safety
  judgments

8
System Validation

• When it is safe to cross, a person monitoring the
  traffic
• scene presses a button
• A second button press means it is no longer safe
  to cross
• The time between button presses specifies a safe
  crossing window
• Use more than one person to compensate for
  individual risk tolerance
• Button press data is synchronized with the video
  data
• Compare system safety estimates to human safety
  judgments

9
Crosswalk Traversal

• While crossing, devotes more processing to the
  right-looking video stream
• Uses a forward-looking camera to detect and stay
  on the marked (zebra striped) crosswalk
• Uses sonar to avoid pedestrians and stopped cars
  on the crosswalk
• Uses a laser range finder to detect the curb cut
  driving over curbs is possible, but undesirable

10
Crosswalk Traversal

• While crossing, devotes more processing to the
  right-looking video stream
• Uses a forward-looking camera to detect and stay
  on the marked (zebra striped) crosswalk
• Uses sonar to avoid pedestrians and stopped cars
  on the crosswalk
• Uses a laser range finder to detect the curb cut
  driving over curbs is possible, but undesirable

11
Related Work

• Automated driving systems CMUs Navlab project,
  Dickmanns autonomous Autobahn vehicle, DARPA
  Challenge
• Traffic scene monitoring systems that analyze
  traffic conditions
• Camera orientation and assumptions of existing
  vision-based, car-tracking systems do not apply
  to street crossing
• Robotic street crossing has not been done
  previously

12
Reasoning about Bounding Boxes

• Larger, lower (in the image plane) bounding boxes
  correspond to close cars
• Smaller, higher bounding boxes denote distant
  cars
• Tracking in real time using Phission so cars move
  very little from frame to frame
• Track individual cars over time to determine
  speed and travel direction
• Need to smooth results over time since CCD
  cameras produce noisy data

13

• Research conducted under the auspices of Dr.
  Holly A. Yanco, the Robotics Lab, and the
  Computer Science Department.
• Contact holly_at_cs.uml.edu for additional
  information.