Object classification via time-varying information inherent in imagery

• US 20050259865A1
• Filed: 11/15/2002
• Published: 11/24/2005
• Est. Priority Date: 11/15/2002
• Status: Abandoned Application

• Current Assignee: Koninklijke Philips Electronics N.V. (Koninklijke Philips N.V.)
• Original Assignee: Koninklijke Philips Electronics N.V. (Koninklijke Philips N.V.)
• Inventors: Philomin, Vasanth, Trajkovic, Miroslav, Gutta, Srinivas
• Application Number:
  US10/295,649
• Publication Number:
  US 20050259865A1
• Time in Patent Office: Days
• US Class Current: 382/156
• CPC Class Codes: G06V 20/40 in video content extracting overlay text G06V20/62; video retrieval G06F16/70; processing of video elementary streams in video servers H04N21/234; processing of video elementary streams in video clients H04N21/44

Abstract

A method for classifying objects in a scene, is provided. The method including: capturing video data of the scene; locating at least one object in a sequence of video frames of the video data; inputting the at least one located object in the sequence of video frames into a time-delay neural network; and classifying the at least one object based on the results of the time-delay neural network.

Claims

1. A method for classifying objects in a scene, the method comprising:

capturing video data of the scene;

locating at least one object in a sequence of video frames of the video data;

inputting the at least one located object in the sequence of video frames into a time-delay neural network; and

classifying the at least one object based on the results of the time-delay neural network.

2. The method of claim 1, wherein the locating comprises performing background subtraction on the sequence of video frames.

3. The method of claim 1, wherein the time-delay neural network is an Elman network.

4. The method of claim 3, wherein the Elman network comprises a Multi-Layer Perceptron with an additional input state layer that receives a copy of activations from a hidden layer at a previous time step as feedback.

5. The method of claim 4, wherein the classifying comprises traversing the state layer to ascertain an overall identity by determining a number of states matched in a model space.

6. A program storage device readable by machine, tangibly embodying a program of instructions executable by the machine to perform method steps for classifying objects in a scene, the method comprising:

capturing video data of the scene;

locating at least one object in a sequence of video frames of the video data;

inputting the at least one located object in the sequence of video frames into a time-delay neural network; and

classifying the at least one object based on the results of the time-delay neural network.

7. The program storage device of claim 6, wherein the locating comprises performing background subtraction on the sequence of video frames.

8. The program storage device of claim 6, wherein the time-delay neural network is an Elman network.

9. The program storage device of claim 8, wherein the Elman network comprises a Multi-Layer Perceptron with an additional input state layer that receives a copy of activations from a hidden layer at a previous time step as feedback.

10. The program storage device of claim 9, wherein the classifying comprises traversing the state layer to ascertain an overall identity by determining a number of states matched in a model space.

11. A computer program product embodied in a computer-readable medium for classifying objects in a scene, the computer program product comprising:

computer readable program code means for capturing video data of the scene;

computer readable program code means for locating at least one object in a sequence of video frames of the video data;

computer readable program code means for inputting the at least one located object in the sequence of video frames into a time-delay neural network; and

computer readable program code means for classifying the at least one object based on the results of the time-delay neural network.

12. The computer program product of claim 11, wherein the computer readable program code means for locating comprises computer readable program code means for performing background subtraction on the sequence of video frames.

13. The computer program product of claim 11, wherein the time-delay neural network is an Elman network.

14. The computer program product of claim 13, wherein the Elman network comprises a Multi-Layer Perceptron with an additional input state layer that receives a copy of activations from a hidden layer at a previous time step as feedback.

15. The Computer program product of claim 14, wherein the computer readable program code means for classifying comprises computer readable program code means for traversing the state layer to ascertain an overall identity by determining a number of states matched in a model space.

16. An apparatus for classifying objects in a scene, the apparatus comprising:

at least one camera for capturing video data of the scene;

a detection system for locating at least one object in a sequence of video frames of the video data and inputting the at least one located object in the sequence of video frames into a time-delay neural network; and

a processor for classifying the at least one object based on the results of the time-delay neural network.

17. The apparatus of claim 16, wherein the detection system performs background subtraction on the sequence of video frames.

18. The apparatus of claim 16, wherein the time-delay neural network is an Elman network.

19. The apparatus of claim 18, wherein the Elman network comprises a Multi-Layer Perceptron with an additional input state layer that receives a copy of activations from a hidden layer at a previous time step as feedback.

20. The apparatus of claim 19, wherein the processor classifies the at least one object by traversing the state layer to ascertain an overall identity by determining a number of states matched in a model space.