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Tracking automobiles using air-borne TLS (Three Line Scanner) images

Tracking Automobiles using Air-borne TLS (Three Line Scanner) Images

Ryuichi Murata, Ryosuke Shibasaki

Center for Spatial Information Science (CSIS)

University of Tokyo

4-6-1 komaba, Meguro-ku, Tokyo 153-8505, Japan

Tel&Fax: +81-3-5452-6417

E-mail:[email protected]yo.ac.jp

Keywords: TLS (three line scanner), air-borne sensor, ITS, object tracking


Abstract:

Acquiring traffic data such as number of cars, speed distribution, number of illegal
parking cars accurately and quickly is needed for ITS (Intelligent Transport System). ITS is
expected to mitigate traffic jam and to improve management of limited road resources. Currently,
as a common practice, only limited traffic data are collected; vehicles are counted using roadside
ultra-sonic sensors. Finding traffic accidents depends on the witness’s notice, patrol of road
administrative officers, and monitoring with roadside cameras. TLS (Three Line Scanner) is an
air-borne sensor consisting of three parallel one-dimensional CCDs mounted on the imaging
plane. It obtains seamless high-resolution images (5-10cm on the ground) with three viewing
directions (fore, nadir, aft) simultaneously mainly to generate 3D spatial data accurately. In
addition, the high-resolution imagery can be applied to observe running cars, speed and parking
cars on the street since TLS scans the same road surface with a time interval with approximately
10 seconds. This paper describes methodologies and the results of applying TLS imagery to the
tracking of automobiles.


1. Introduction

ITS (Intelligent Transport System) society will spread in near the future. ITS is expected to
operate traffic flows and to provide efficient road administration. But generally, acquiring traffic
data depends on roadside ultra-sonic detectors, cameras, witness’s notices or patrols of road
administrative officers. Traffic data acquired with such devices are basically point-based and fail
to represent spatial distribution. It is quite necessary to develop a method of acquiring traffic data
such as number of cars, speed distribution, finding accidental vehicles accurately and quickly
over large areas. The high-resolution imagery of TLS (Three Line Scanners) can be applied to the
observation of running cars, their speed and parking cars on the street because TLS can scan the
same road surface and objects with a time interval with approximately 10 seconds.


2. TLS system


2.1 TLS principle

TLS (Three Line Scanner) is an air-borne sensor consisting of three parallel one-dimensional
CCDs mounted on the imaging plane (Fig.1 and Fig.2). It obtains seamless high-resolution
images (5-10cm on the ground) with three viewing directions (fore, nadir, aft) simultaneously
mainly to generate 3D spatial data accurately with RTK-GPS and INS.


Fig.1: Method of TLS image Acquiring


Fig.2: Plain TLS image


2.2 TLS performance


Table1: system specification of TLS

CCD Number of pixel/line 10200 pixels
Pitch of pixel 7 um
Number of CCD 3(monochrome), 1(RGB)
Number of shading 12 bit
Lens Distance of focus 60mm
Angle of stereo 21°
Frequency 500 line/second


2.3 TLS characteristics

Characteristics of TLS are summarized as follows.

  1. Seamless high-resolution images (5-10cm on the ground, about aerial photograph class) can
    be obtained with three different viewing directions (fore, nadir, aft). Easy to create
    ortho-image from TLS images because TLS images are “line-projection” and less distorted
    than conventional aerial photo-images, which is point-projection image.
  2. Much less ground control point is needed since RTK-GPS and INS can estimate the sensor
    position and attitude accurately.
  3. TLS system records digital data directly, which enable users to easily process and analyze
    them on the real-time basis and help minimize processing errors.
  4. Multi-spectrum images can be acquired by replacing the filters and sensors.

 

 

ACRS 2000

 

Poster Session 1
Tracking Automobiles using Air-borne TLS (Three Line Scanner) Images

3. Automobile tracking method

We examined two automobile tracking methods using TLS gray scale image.


3.1 brightness difference from a pair of images

Since moving objects on the road are only automobiles, it is possible to track automobile
objects using differential image from a pair of image covering the same area at the different times
(Fig.3). We calculate object’s speed by dividing the ground distance of centroids of each object by
time difference. Fig.3 shows a result of tracking a white bus. But any automobiles whose color is
similar to road surface are not tracked. In addition, we can’t apply this method to track standing
automobiles due to a traffic jam or an accident.


Fig.3: Differential image and a pair of image covered the same area at the different times


3.2 Template matching

In order to track stopping automobiles, I used template matching method using Hausdorff
distance. First operation in the processing is edge detection from TLS image. Secondary is
making a proper size rectangle template according to altitude of a platform or image resolution
since all automobiles in aerial images have rectangular shape. Last one is affine transformation of
TLS image and template matching. We narrowed down the operation image area to roads to
improve the accuracy of the matching.

The distance between the each pixel of the template and the nearest TLS edge point defines the
Hausdorff distance. We detected template position whose summation of each points Hausdorff
distance is under set threshold as automobile object.


Fig.4: Detected objects by template matching


4. Conclusions

This study show that it is possible to track automobiles using TLS gray scale image.
Differential image method depends on brightness of TLS image, so automobiles whose colors are
similar to those of road surfaces were not tracked. It is difficult to detect edge in template
matching method since the test image is experimental with no enough quality. Further studies are
required to improve the accuracy of tracking objects using color image and high resolution image
from the TLS.


References

  • Shunji Murai, Yositaka Matsumoto, Li Xun, 1995, stereoscopic imagery with an air borne
    three-line scanner (TLS), ISPRS commission V, Intercom mission Workshop, pp20-25
  • Michihiro Murao, Yasuyuki Matsushita, Katsushi Ikeuchi, Masao Sakauchi, 2000, Visualization
    of traffic Conditions for Drivers, UM3’2000 session D, p22