Method for Automatically Classifying Moving Vehicles

• US 20140176679A1
• Filed: 12/20/2013
• Published: 06/26/2014
• Est. Priority Date: 12/21/2012
• Status: Abandoned Application

• Current Assignee: Jenoptik Robot GmbH (Jenoptik AG)
• Original Assignee: Jenoptik Robot GmbH (Jenoptik AG)
• Inventors: LEHNING, Michael
• Application Number:
  US14/136,527
• Publication Number:
  US 20140176679A1
• Time in Patent Office: Days
• US Class Current: 348/46
• CPC Class Codes: G06V 20/54 of traffic, e.g. cars on the road, trains or boats
• CPC Class Codes: G06V 20/625 License plates
• CPC Class Codes: G06V 20/647 by matching two-dimensional images to three-dimensional objects
• CPC Class Codes: H04N 13/275 from 3D object models, e.g. computer-generated stereoscopic image signals

Abstract

The invention is directed to a method for classifying a moving vehicle. The object of the invention is to find a novel possibility for classifying vehicles moving in traffic which allows a reliable automatic classification based on two-dimensional image data. This object is met according to the invention in that an image of a vehicle is recorded by means of a camera and the position and perspective orientation of the vehicle are determined therefrom, rendered two-dimensional views are generated from three-dimensional vehicle models which are stored in a database in positions along an anticipated movement path of the vehicle and are compared with the recorded image of the vehicle, and the vehicle is classified from the two-dimensional view found to have the best match by assignment of the associated three-dimensional vehicle model.

Claims

1. A method for classifying a moving vehicle comprising the following method steps:

recording at least one image of a vehicle by means of a camera and determining position and perspective orientation of the vehicle,

generating from three-dimensional vehicle models which are stored in a database rendered two-dimensional views in positions and perspective orientations in which the three-dimensional vehicle model could be perspectively orientated along an anticipated movement path of the vehicle relative to the camera,

comparing the at least one recorded image of the vehicle with the rendered two-dimensional views of the stored three-dimensional vehicle models and finding the two-dimensional view with the best match, and

classifying the recorded vehicle with the three-dimensional vehicle model which best matches one of the two-dimensional views.

2. The method according to claim 1, wherein the image is recorded in an installation position of the camera with a known distance and horizontal angle from the edge of a roadway over which the vehicle is moving and with a known vertical angle of the camera relative to the surface of the roadway.

3. The method according to claim 1, wherein in the perspective orientation, the position and the dimension of the recorded vehicle are determined by means of an image sequence comprising at least two images.

4. The method according to claim 1, wherein in a prior step for rendering the three-dimensional vehicle models corresponding to the perspective orientation and the dimension, an image sequence of a recorded reference vehicle is captured and an image is selected therefrom at a selected position relative to the installation position of the camera, wherein two-dimensional views are rendered from a plurality of three-dimensional vehicle models for the selected position and are stored in a storage.

5. The method according to claim 4, wherein in a prior step for rendering the three-dimensional vehicle models corresponding to the perspective orientation and the dimension, a plurality of images are selected from the image sequence of a recorded reference vehicle at a plurality of selected positions of the vehicle relative to the installation position, wherein two-dimensional views of a plurality of three-dimensional vehicle models are rendered respectively for each of these selected positions and are stored in a storage.

6. The method according to claim 5, wherein an interpolation is possible between two adjacent two-dimensional views of the plurality of two-dimensional views so that the comparison of the recorded vehicle with the two-dimensional views can be performed independent from the specifically selected position of the perspective orientation of the vehicle.

7. The method according to claim 1, wherein a reduced-data image section with evaluatable geometric structures is selected from the rendered two-dimensional views of all of the three-dimensional vehicle models, and an image portion corresponding to the reduced-data image section of the rendered two-dimensional views is extracted from the at least one recorded image of the vehicle.

8. The method according to claim 1, wherein the recorded vehicle is captured in at least one image in a perspective orientation with a license plate or other characteristic geometrical structures through selection of the installation position of the camera.

9. The method according to claim 8, wherein a rectification of the license plate is carried out based on the horizontal angle and vertical angle known from the installation position in order to automatically implement an optical character recognition (OCR).

10. The method according to claim 1, wherein the positions and dimensions of the recorded vehicle are determined by evaluating signals of a radar device.

11. The method according to claim 1, wherein the three-dimensional vehicle models in the database are in the form of three-dimensional textured surface nets, wherein geometric structures are defined at the surface and in the interior of the three-dimensional vehicle models.

12. The method according to claim 11, wherein at least one passenger sitting position is defined in the interior of the three-dimensional vehicle models as a geometric structure of the three-dimensional vehicle models.

13. The method according to claim 6, wherein the extraction of reduced-data image sections is carried out corresponding to the geometric structures defined at the three-dimensional vehicle models.

14. The method according to claim 1, wherein a more accurate representation of detail can be achieved in darker areas of the reduced-data image sections by applying a histogram match which is applied either to the image as a whole or in a locally adaptive manner.

15. The method according to claim 1, generating the rendered two-dimensional views comprises:

compiling a database of three-dimensional vehicle models of a wide variety of vehicle types, wherein geometric structures are defined at the three-dimensional vehicle models and are provided for an evaluation,

determining a camera position for capturing vehicles moving in circulating traffic on a roadway by means of a camera, wherein at least one image is captured at a known distance, angle and a known height with respect to the roadway so that a perspective orientation and the dimension of the vehicles to be recorded is predetermined,

orienting and dimensioning the three-dimensional vehicle models of the database corresponding to the movement path with fixed camera position and distance from the roadway, and

generating and storing two-dimensional views of the three-dimensional vehicle models by rendering the oriented and dimensioned three-dimensional vehicle models from the database.