Computer-implemented method for automated object recognition and classification in scenes using segment-based object extraction

• US 20080123959A1
• Filed: 06/25/2007
• Published: 05/29/2008
• Est. Priority Date: 06/26/2006
• Status: Abandoned Application

• Current Assignee: Keystream Corp.
• Original Assignee: Keystream Corp.
• Inventors: Cullen, Schuyler A., Ratner, Edward R.
• Application Number:
  US11/821,767
• Publication Number:
  US 20080123959A1
• Time in Patent Office: Days
• US Class Current: 382/173
• CPC Class Codes: G06V 10/267 by performing operations on regions, e.g. growing, shrinking or watersheds
• CPC Class Codes: G06V 10/40 Extraction of image or video features

Abstract

One embodiment relates to a computer-implemented method for automated object recognition and classification in scenes using segment-based object extraction. The method includes automated procedures for receiving video images, creating segmentation maps from said images, grouping segments so as to form extracted objects, extracting features from said extracted objects, classifying said extracted objects using said features. Other features, aspects and embodiments are also disclosed.

Claims

1. A computer-implemented method for automated image object recognition and classification, the method comprising:

receiving video images;

creating segmentation maps from said images;

grouping segments so as to form extracted objects;

extracting features from said extracted objects; and

classifying said extracted objects using the features.

2. The method of claim 1, wherein extracting features from an extracted object comprises:

loading a pixel mask of the extracted object; and

selecting keypoints using a keypoint selection technique which is applied only to pixels belonging to the extracted object.

3. The method of claim 2, wherein extracting features from the extracted object further comprises:

calculating keypoint region descriptors; and

creating feature vector sets from said descriptors.

4. The method of claim 1, wherein classifying said extracted objects comprises:

inputting said feature vector sets; and

applying a classifier to said feature vector sets which identifies object classes based on said feature vector sets.

5. A computer apparatus configured for automated image object recognition and classification, the apparatus comprising:

a processor for executing computer-readable program code;

memory for storing in an accessible manner computer-readable data;

computer-readable program code configured to receive video images;

computer-readable program code configured to create segmentation maps from said images;

computer-readable program code configured to group segments so as to form extracted objects;

computer-readable program code configured to extract features from said extracted objects; and

computer-readable program code configured to classify said extracted objects using the features.

6. The apparatus of claim 5, wherein the computer-readable program code to extract features is further configured to load a pixel mask of the extracted object, and to select keypoints using a keypoint selection technique which is applied only to pixels belonging to the extracted object.

7. The apparatus of claim 6, wherein the computer-readable program code to extract features is further configured to calculate keypoint region descriptors, and to create feature vector sets from said descriptors.

8. The apparatus of claim 5, wherein the computer-readable program code to classify said extracted objects is further configured to input said feature vector sets and to apply a classifier to said feature vector sets which identifies object classes based on said feature vector sets.