METHOD AND SYSTEM FOR CLASSIFICATION OF MOVING OBJECTS AND USER AUTHORING OF NEW OBJECT CLASSES

• US 20130268476A1
• Filed: 12/24/2010
• Published: 10/10/2013
• Est. Priority Date: 12/24/2010
• Status: Abandoned Application

• Current Assignee: Hewlett-Packard Development Company, L.P. (HP Inc.)
• Original Assignee: Hewlett-Packard Development Company, L.P. (HP Inc.)
• Inventors: Munnangi, Krusheel, Subramanian, Anbumani, Banerjee, Serene, Sankarasubramniam, Yogesh, Sharma, Avinash
• Application Number:
  US13/995,121
• Publication Number:
  US 20130268476A1
• Time in Patent Office: Days
• US Class Current: 706/46
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation
• CPC Class Codes: G06V 40/20 Movements or behaviour, e.g. gesture recognition recognition of facial expressions G06V40/16

Abstract

A system and method for classification of moving objects and user authoring of new object classes is disclosed. In one embodiment, in a method of classification of moving objects, a moving object is inputted. Then, an object descriptor and a motion descriptor are extracted from the inputted moving object. Multiple initial candidate library object descriptors are identified from an object library and a motion library using the extracted object descriptor and the extracted motion descriptor. An initial object class estimate is identified based on the identified multiple initial candidate library object descriptors. Then, an initial residue is computed based on the extracted object descriptor and the identified multiple initial candidate library object descriptors associated with the initial object class estimate. The object class estimates are iteratively identified and it is determined whether the object class estimates converge based on a stopping criterion.

Claims

1. A computer-implemented method for classification of moving objects, comprising:

inputting a moving object;

extracting an object descriptor and a motion descriptor from the inputted moving object;

identifying multiple initial candidate library object descriptors from an object library and a motion library using the extracted object descriptor and the extracted motion descriptor, and wherein the object library and motion library are formed from given object samples comprising known object classes;

identifying an initial object class estimate based on the identified multiple initial candidate library object descriptors;

computing an initial residue based on the extracted object descriptor and the identified multiple initial candidate library object descriptors associated with the initial object class estimate; and

iteratively identifying object class estimates and determining whether the object class estimates converge based on a stopping criterion.

2. The computer-implemented method of claim 1, wherein iteratively identifying the object class estimates and determining whether the object class estimates converge based on the stopping criterion comprises:

identifying a set of multiple candidate object descriptors from the object library based on a residue and the identified multiple candidate library object descriptors from a previous iteration;

computing scores for each object class based on the identified set of multiple candidate library object descriptors;

identifying an object class estimate with a highest score;

computing a residue based on the extracted object descriptor and the identified candidate library object descriptors associated with the identified object class estimate; and

determining whether the identified object class estimates converge based on the stopping criterion.

3. The computer-implemented method of claim 2, further comprising:

if the stopping criterion is satisfied, determining whether to reject the inputted moving object based on an object rejection criterion.

4. The computer-implemented method of claim 3, further comprising:

if the inputted object is not to be rejected, declaring the identified object class as an output object class.

5. The computer-implemented method of claim 1, further comprising:

authoring an object class by a user through addition of an object library and a motion library associated with the object class to existing object library and motion library, respectively.

6. The computer-implemented method of claim 5, further comprising:

determining whether the authored object class by the user is to be rejected;

if so, rejecting the authored object class and requesting the user for an alternate object class; and

if not, adding the object library and the motion library associated with the authored object class to the existing object library and motion library, respectively.

7. The computer-implemented method of claim 1, wherein the object descriptor and the motion descriptor are selected from the group comprising of features describing shape, size, color, temperature, motion, and intensity of the inputted moving object.

8. A system for classification of static objects and dynamic objects, comprising:

a processor;

memory coupled to the processor;

wherein the memory includes a moving object classification module having instructions to;

input a moving object;

extract an object descriptor and a motion descriptor from the inputted moving object;

identify multiple initial candidate library object descriptors from an object library and a motion library using the extracted object descriptor and the extracted motion descriptor, and wherein the object library and motion library are formed from given object samples comprising known object classes;

identify an initial object class estimate based on the identified multiple initial candidate library object descriptors;

compute an initial residue based on the extracted object descriptor and the identified multiple initial candidate library object descriptors associated with the initial object class estimate; and

iteratively identify object class estimates and determine whether the object class estimates converge based on a stopping criterion.

9. The system of claim 8, wherein the moving object classification module has further instructions to determine whether to reject the inputted moving object based on an object rejection criterion if the stopping criterion is satisfied.

10. The system of claim 9, wherein the moving object classification module has further instructions to declare the identified object class as an output object class if the inputted object is not to be rejected.

11. The system of claim 10, wherein the moving object classification module has further instructions to author an object class by a user through addition of an object library and a motion library associated with the object class to existing object library and motion library, respectively.

12. The system of claim 11, wherein the moving object classification module has further instructions to determine whether the authored object class by the user is to be rejected, to reject the authored object class and request the user for an alternate object class if it is determined so, and to add the object library and the motion library associated with the authored object class to the existing object library and motion library, respectively if it is determined not.

13. A non-transitory computer readable storage medium for classification of moving objects having instructions that, when executed by a computing device causes the computing device to:

input a moving object;

extract an object descriptor and a motion descriptor from the inputted moving object;

identify multiple initial candidate library object descriptors from an object library and a motion library using the extracted object descriptor and the extracted motion descriptor, and wherein the object library and motion library are formed from given object samples comprising known object classes;

identify an initial object class estimate based on the identified multiple initial candidate library object descriptors;

compute an initial residue based on the extracted object descriptor and the identified multiple initial candidate library object descriptors associated with the initial object class estimate; and

iteratively identify object class estimates and determining whether the object class estimates converge based on a stopping criterion.

14. The non-transitory computer readable storage medium of claim 13, further comprising instructions to author an object class by a user through addition of an object library and a motion library associated with the object class to existing object library and motion library, respectively.

15. The non-transitory computer readable storage medium of claim 14, wherein the object descriptor and the motion descriptor are selected from the group comprising of features describing shape, size, color, temperature, motion, and intensity of the inputted moving object.