Object posture estimation/correlation system using weight information

• US 7,706,601 B2
• Filed: 08/27/2004
• Issued: 04/27/2010
• Est. Priority Date: 08/29/2003
• Status: Active Grant

• Current Assignee: NEC Corporation
• Original Assignee: NEC Corporation
• Inventors: Hamanaka, Masahiko
• Primary Examiner(s): Mariam; Daniel G
• Assistant Examiner(s): Woldemariam; Aklilu k
• Application Number:
  US10/570,128
• Publication Number:
  US 20060165293A1
• Time in Patent Office: 2,069 Days
• Field of Search: 382/154, 382/209, 382/103
• US Class Current: 382/154
• CPC Class Codes: G06T 2207/30201 Face
• CPC Class Codes: G06T 7/75 involving models
• CPC Class Codes: G06V 40/161 Detection; Localisation; Normalisation

Abstract

An object pose estimating and matching system is disclosed for estimating and matching the pose of an object highly accurately by establishing suitable weighting coefficients, against images of an object that has been captured under different conditions of pose, illumination. Pose candidate determining unit determines pose candidates for an object. Comparative image generating unit generates comparative images close to an input image depending on the pose candidates, based on the reference three-dimensional object models. Weighting coefficient converting unit determines a coordinate correspondence between the standard three-dimensional weighting coefficients and the reference three-dimensional object models, using the standard three-dimensional basic points and the reference three-dimensional basic points, and converts the standard three-dimensional weighting coefficients into two-dimensional weighting coefficients depending on the pose candidates. Weighted matching and pose selecting unit calculates weighted distance values or similarity degrees between said input image and the comparative images, using the two-dimensional weighting coefficients, and selects one of the comparative images whose distance value up to the object is the smallest or whose similarity degree with respect to the object is the greatest, thereby to estimate and match the pose of the object.

Claims

1. An object pose estimating and matching system comprising:

reference three-dimensional object model storage means for storing, in advance, reference three-dimensional object models of objects;

standard three-dimensional weighting coefficient storage means for storing, in advance, standard three-dimensional weighting coefficients;

reference three-dimensional basic point storage means for storing, in advance, reference three-dimensional basic points corresponding to said reference three-dimensional object models;

standard three-dimensional basic point storage means for storing, in advance, standard three-dimensional basic points corresponding to standard three-dimensional object models;

pose candidate determining means for determining pose candidates for an object;

comparative image generating means for generating comparative images close to an input image depending on said pose candidates, based on said reference three-dimensional object models;

weighting coefficient converting means for determining a coordinate correspondence between said standard three-dimensional weighting coefficients and said reference three-dimensional object models, using said standard three-dimensional basic points and said reference three-dimensional basic points, and converting said standard three-dimensional weighting coefficients into two-dimensional weighting coefficients depending on said pose candidates; and

weighted matching and pose selecting means for calculating weighted distance values or similarity degrees between said input image and said comparative images, using said two-dimensional weighting coefficients, and selecting one of the comparative images whose distance value up to said object is the smallest or whose similarity degree with respect to said object is the greatest, thereby to estimate and match the pose of said object.

3. An object pose estimating and matching system according to claim 1, further comprising:

three-dimensional object model registering means for registering reference three-dimensional object models in said reference three-dimensional object model storage means; and

three-dimensional basic point registering means for determining reference three-dimensional basic points with respect to said reference three-dimensional object models, and registering the determined reference three-dimensional basic points in said reference three-dimensional basic point storage means.

2. An object pose estimating and matching system comprising:

reference three-dimensional object model storage means for storing, in advance, reference three-dimensional object models of objects;

variation-specific standard three-dimensional weighting coefficient storage means for storing, in advance, standard three-dimensional weighting coefficients corresponding to image variations;

reference three-dimensional basic point storage means for storing, in advance, reference three-dimensional basic points corresponding to said reference three-dimensional object models;

standard three-dimensional basic point storage means for storing, in advance, standard three-dimensional basic points corresponding to standard three-dimensional object models;

pose candidate determining means for determining pose candidates for an object;

variation estimating means for determining a correspondence between an area of a three-dimensional object model and an input image, using said pose candidates and said reference three-dimensional object models, and estimating a variation based on image information of a given area of said input image;

comparative image generating means for generating comparative images close to said input image depending on said pose candidates, based on said reference three-dimensional object models;

weighting coefficient converting means for determining a coordinate correspondence between said standard three-dimensional weighting coefficients corresponding to the estimated variation and said reference three-dimensional object models, using said standard three-dimensional basic points and said reference three-dimensional basic points, and converting said standard three-dimensional weighting coefficients into two-dimensional weighting coefficients depending on said pose candidates; and

weighted matching and pose selecting means for calculating weighted distance values or similarity degrees between said input image and said comparative images, using said two-dimensional weighting coefficients, and selecting one of the comparative images whose distance value up to said object is the smallest or whose similarity degree with respect to said object is the greatest, thereby to estimate and match the pose of said object.