System and method for image mapping and visual attention

• US 7,835,820 B2
• Filed: 10/11/2006
• Issued: 11/16/2010
• Est. Priority Date: 10/11/2005
• Status: Expired due to Fees

• Current Assignee: Vanderbilt University
• Original Assignee: Vanderbilt University
• Inventors: Peters, Richard A. II
• Primary Examiner(s): Nguyen; Kim T
• Application Number:
  US11/546,867
• Publication Number:
  US 20090254236A1
• Time in Patent Office: 1,497 Days
• Field of Search: 700/245, 700/246, 700/250, 700/253, 700/254, 700/258, 701/1, 701/24, 701/25, 701/36, 701/213, 706/45, 706/903
• US Class Current: 700/245
• CPC Class Codes: G05D 1/0221 involving a learning process
• CPC Class Codes: G05D 1/0227 using mechanical sensing means, e.g. for sensing treated area
• CPC Class Codes: G05D 1/024 in combination with a laser lasers per se H01S
• CPC Class Codes: G05D 1/0246 using a video camera in combination with image processing means
• CPC Class Codes: G05D 1/0255 using acoustic signals, e.g. ultra-sonic singals sonar systems designed for anti-collision purposes G01S15/93
• CPC Class Codes: G05D 1/0257 using a radar radar systems designed for anti-collision purposes between land vehicles or between land vehicle and fixed obstacles G01S13/931
• CPC Class Codes: G05D 1/0259 using magnetic or electromagnetic means
• CPC Class Codes: G05D 1/027 comprising intertial navigation means, e.g. azimuth detector inertial navigation G01C21/16; inertial navigation combined with non-inertial navigation instruments G01C21/165
• CPC Class Codes: G05D 1/0274 using mapping information stored in a memory device navigation using map-matching G01C21/30
• CPC Class Codes: G05D 1/0278 using satellite positioning signals, e.g. GPS
• CPC Class Codes: G06V 10/462 Salient features, e.g. scale invariant feature transforms [SIFT]
• CPC Class Codes: G06V 20/35 Categorising the entire scene, e.g. birthday party or wedding scene

Abstract

A method is described for mapping dense sensory data to a Sensory Ego Sphere (SES). Methods are also described for finding and ranking areas of interest in the images that form a complete visual scene on an SES. Further, attentional processing of image data is best done by performing attentional processing on individual full-size images from the image sequence, mapping each attentional location to the nearest node, and then summing attentional locations at each node.

Claims

1. An adaptive autonomous robot comprising:

sensors to generate signals that can be mapped to a characteristic of an environment surrounding the robot;

actuators to enable the robot to perform an action;

a camera for receiving image data from an external source;

a database for associating received image data with points on a portion of a spherical region centered on the robot;

means for performing attentional processing on individual images to identify attentional locations;

means for mapping each attentional location to a nearest point on the portion of the spherical region; and

a summer for summing activation values of the attentional locations mapped to a point.

2. The robot of claim 1 wherein the sensors comprise:

means for sensing an internal state of the robot; and

means for sensing one or more characteristics of the robot'"'"'s environment.

3. The robot of claim 2 wherein the database comprises a sensory ego sphere for representing an object based on the sensed internal state and the sensed environment.

4. In an adaptive autonomous robot comprising:

sensors to generate signals that can be mapped to a characteristic of an environment surrounding the robot;

actuators to enable the robot to perform an action;

a camera for receiving image data from an external source; and

a database for associating received image data with points on a portion of a spherical region centered on the robot;

a method of finding and ranking areas of interest in images from the external source comprising;

performing attentional processing on individual images to identify attentional locations;

mapping each attentional location to a nearest point on the portion of the spherical region; and

summing activation values of the attentional locations mapped to a point.

5. An adaptive autonomous robot, comprising:

sensors to generate signals that can be mapped to a characteristic of an environment surrounding the robot;

actuators to enable the robot to perform an action;

a camera to receive image data from an external source;

a database to associate received image data with points on a portion of a spherical region centered on the robot;

an attention agent to perform attentional processing on individual images to identify attentional locations; and

a summer to sum activation values of the attentional locations mapped to a point wherein each attentional location is mapped to a nearest point on the portion of the spherical region.