Recognition of 3D objects
3D objects in the form of human faces are recognised at or adjacent an entrance to a building. Cameras are spaced horizontally from one another in an array to provide multiple viewpoints of a common scene with overlapping fields of view. For each of the cameras, a sequence of images of a face is generated and each of those images is normalised to a canonical view. One or more best normalised image for each camera is selected and feature data is extracted from the selected image. A recognition processor compares the extracted feature data of each selected image with stored, corresponding feature data of known 3D objects. A recognition result is output when the extracted feature data of at least one of the selected images corresponds to stored, corresponding feature data of at least one of the known 3D objects.
1. A method of recognising a 3D object at a scene, comprising the steps of:
providing an array of cameras that are spaced horizontally from one another such that the cameras provide multiple viewpoints of a scene with overlapping fields of view;
for each of the cameras, generating a sequence of images of a 3D object at the scene, normalising each of those images to a canonical view that is the same canonical view for each of the cameras, selecting one or more best normalised image for that camera and passing the or each selected image to a feature extraction processor;
extracting feature data from each of the selected images using a feature extraction processor;
comparing the extracted feature data of each of the selected images with stored, corresponding feature data of known 3D objects using a recognition processor; and
outputting a recognition result when the extracted feature data of at least one of the selected images corresponds to stored, corresponding feature data of at least one of the known 3D objects.
2. A method according to claim 1 wherein, for each camera, an image is passed to the feature extraction processor only if that image is better than a predetermined threshold.
3. A method according to claim 1 , comprising the further step of receiving all selected images from all of the cameras and carrying out a further selection from those images to select one or more best normalised image that is passed to the feature extraction processor.
4. A method according to claim 1 , wherein the cameras are disposed at one side of the scene.
5. A method according to claim 1 , wherein the cameras surround the scene.
6. A method according to claim 1 , wherein the cameras are arranged in an arc as seen in plan view.
7. A method according to claim 1 , wherein the scene has a floor and camera apertures are located at a height above the floor that is in a range 1.5 to 2.5 metres or 3 to 4 metres.
8. A method according to claim 1 , wherein the scene has a floor and camera apertures are located at a height above the floor that is less than 5 metres.
9. A method according to claim 1 , wherein a maximum distance between any two cameras of the array is at least 2 metres.
10. A method according to claim 1 , wherein the array of cameras comprises at least three, four or five cameras.
11. A method according to claim 1 , wherein the scene is at a location where people travel in a common direction.
12. A method according to claim 1 , wherein the 3D object to be recognised is a human subject.
13. A method according claim 12 , wherein the 3D object to be recognised is a human face.
14. A method according to claim 1 , wherein said canonical view is a frontal view.
15. A method according to claim 1 , wherein the cameras are 2D cameras.
16. A method according to claim 1 , wherein the step of normalising images to a canonical view comprises synthesising a canonical viewpoint image from images of different viewpoints from different ones of the cameras.
17. A system for use in a method according to claim 1 , the system including the array of cameras that are spaced from one another such that the cameras provide multiple viewpoints of the scene with overlapping fields of view; for each of the cameras, means for generating a sequence of images of the object, normalising each of those images to a canonical view and selecting at least one best normalised image for that camera; the feature extraction processor; the recognition processor; a data store that stores said corresponding feature data of known 3D objects; and an output device to output said recognition result: the system being configured to perform a method according to claim 1 .