Pedestrian Detection with Radar and Computer Vision

Transcription

1 Pedestrian Detection with Radar and Computer Vision camera radar sensor Stefan Milch, Marc Behrens, Darmstadt, September / 26, 2001

2 Pedestrian accidents and protection systems Impact zone: 10% opposite roadway 70% 17% border of roadway Active pedestrian protection systems: lift bonnet in case of collision bonnet airbag active bumper (active soft nose) lower front spring strut (off-road-vehicles) 3% Source: Pedestrian injury accidents - Report by WG 7 of the European Experimental Vehicles Committee, 1982 Future aim: Driver assistance system to avoid the accident

3 Properties of the radar sensor 2D Space objects 3-dB detection field sensors

4 Properties of the radar sensor 2D Space objects Result of measurement Sensor principle Radar List of reflection-points (range, angle, velocity, RCS) Active Data rate Low 3-dB detection field Object detection Object properties Clustering of reflection-points (without model) Location, velocity, RCS, (dimension)

5 Properties of the video-sensor 3D space camera target 2D space camera Result of measurement Sensor principle Data rate Object detection Object properties Video Gray-level matrix (brightness distribution) Passive High Knowledge based interpretation (with model) Model depending (derived from gray-level matrix)

6 Sensor Fusion / Sensor Combination Purpose of sensor fusion: Merge data coming from different information sources. Target Type Radar Target Location Video No perfect sensor: use smart combination to get favorable properties of one sensor and to suppress disadvantages Aim: Obtain information of greater quality; definition of «greater quality» will depend upon application

7 Topology of the pedestrian detection system radar camera Vehicle: v eigen target list ( r v,ϕ ), rel,steering track targets image pre-selection criteria: r, v, (dimension) examined hypothesis list examination of pedestrian hypotheses hypothesis list time based stabilization track hypotheses results pedestrian list Application(s) Sensing Perception

8 Generation of hypotheses hypotheses camera model projection Image space

9 Generation of hypotheses hypotheses hypotheses Image plane camera model projection Classification (Computer Vision) projection Image space

10 Pedestrian Model: What to Look For What forms of representations are suitable for the perception of dynamic visual objects such as moving persons? Model Matching Image Mask Mask from from a a particular particular pedestrian pedestrian // pose pose Meaningful perception requires a priori knowledge Some kind of simplifying assumptions are generally required Dimensionality of model-space (Computational expense) Generic Generic deformable deformable 3D 3Dparametric surface surface representation representation

11 Pedestrian Model: Approach taken 2D outline of human is modeled View based shape models Statistical Shape Model Nearest edge on Normal (x,y ) Model Point (x,y) Side view Normal to Model Boundary Image Object Model Boundary Front/back view

12 Outlook and conclusion «Sensor» that recognizes pedestrians is the assumption for an active protection system Sensors and parts of signal processing can support more applications like, adaptive cruise control (ACC) pre-crash detection Feasibility of the approach was shown, Performance analyzes, enhancements and optimization under examination