US 7,333,133 B2Granted

Recursive least squares approach to calculate motion parameters for a moving camera

AssigneeSpatial Integrated Systems, Inc.

InventorsSamuel Henry Chang, J. Joseph Fuller, Ali Farsaie, Leslie Ray Elkins

Life of this patent

Estimating the term…

Loading patent…

Abstract

A method and system for estimating camera motion parameters and determining a filter to correct for camera motion errors. The estimating method and system includes obtaining an observation point set including a plurality of observed point vectors, computing a plurality of motion output vectors by performing a recursive least squares (RLS) process based on a plurality of motion parameter vectors, and comparing the plurality of motion output vectors to the plurality of observed point vectors. The filter determining method and system includes determining a plurality of desired motion point vectors, computing a plurality of estimated motion point vectors by means of an RLS algorithm, and computing the filter based on a difference between the plurality of estimated motion point vectors and the plurality of desired motion point vectors.

Claims17

Dependent claims

A method for estimating camera motion parameters, the method comprising:

obtaining an observation point set including a plurality of observed point vectors;
computing a plurality of motion output vectors by performing a recursive least squares (RLS) process based on a plurality of motion parameter vectors;
and,
comparing the plurality of motion output vectors to the plurality of observed point vectors;
wherein the computing a plurality of motion output vectors and the comparing the plurality of motion output vectors to the plurality of observed point vectors comprise:
initializing a first covariance matrix to a positive value;
setting a first motion parameter estimate vector to an initial value;
determining each of the plurality of motion parameter vectors, the determining comprising:
computing a current covariance matrix;
computing a current motion parameter estimate vector based on the current covariance matrix;
computing a current motion output vector and a current state variable matrix based on the current covariance matrix;
and,
comparing the current motion output vector to the observation point set;
and, repeating the determining a predetermined number of times;
wherein:
the computing a current covariance matrix comprises computing Pt=Pt−1+Pt−1φt[I+φt′Pt−1φt]−1φt−1′Pt−2, Pt being the current covariance matrix, Pt−1 being the prior current covariance matrix, Pt−2 being the second prior current covariance matrix, φt being the current state variable matrix, φt−1 being the prior current state variable matrix, and I being the identity matrix;
and,
the computing a current motion parameter estimate vector comprises computing {circumflex over (θ)}t={circumflex over (θ)}t−1+[Pt−1φt[I+φ1′Pt−1φt]−1][yt−φt{circumflex over (θ)}t−1], {circumflex over (θ)}t being the current motion parameter estimate, {circumflex over (θ)}t−1 being the prior current motion parameter estimate, and y, being the current motion output vector.

15 more elements

A method for determining a filter to correct for camera motion errors, the method comprising:

determining a plurality of desired motion point vectors;
computing a plurality of estimated motion point vectors by means of an RLS algorithm;
and,
computing the filter based on a difference between the plurality of estimated motion point vectors and the plurality of desired motion point vectors,
wherein:
the determining a plurality of desired motion point vectors comprises determining the desired motion as described by Xt+1=RdXt+Td, where Xt is the motion output matrix at time t, Xt−1 is the motion output matrix at time t+1, Rd is the desired rotation matrix, and Td is the desired translation vector;
the computing a plurality of estimated motion point vectors comprises computing the estimated motion as described by Xt−1=ReXt+Te+cee, where Re is the estimated rotation matrix, Te is the estimated translation vector, ce is a noise transformation matrix, and e is a random noise vector;
and,
the computing the filter comprises:
computing a filter rotation matrix according to Rf=Re −Rd;
and,
computing a filter translation vector according to Tf=Te−Td.

9 more elements

A system for estimating and filtering camera motion parameters, the system comprising:

a movable digital camera for generating a plurality of 2-dimensional images of a scene or object;
a control means for translating and rotating the camera along a predetermined trajectory;
a computer system for receiving and processing the plurality of 2-dimensional images, the computer system including:
a user interface for receiving instructions from a user and for providing output to a user;
an image input means for receiving the plurality of 2-dimensional images from the camera;
a storage means for storing programs and the plurality of images;
a program to determine a desired motion, the desired motion described by Xt+1=RdXt+Td, where Xt is the motion output matrix at time t, Xt+1 is the motion output matrix at time t+1, Rd is the desired rotation matrix, and Td is the desired translation vector;
and,
a program to compute an estimated motion by means of an RLS program, the estimated motion described by Xt+1=ReXt+Te+cee, where Re is the estimated rotation matrix, Te is the estimated translation vector, ce is a noise transformation matrix, and e is a random noise vector.

6 more elements

Dependencies are inferred from the claim text.

Facts

Application: 10/814,711Filed 31 Mar 2004
Published: US 2004/0257452 A123 Dec 2004
Granted: 19 Feb 2008
Term ends: Not estimatedThe source records don’t support an estimate.

Classification3 codes

G06T 7/246
Analysis of motion: using feature-based methods, e.g. the tracking of corners or segments
G06T 7/80
Image analysis: analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration
G06T
Image data processing or generation, in general

Family

US 2004/0257452 A1Pre-grant publication · published 23 Dec 2004
US 7,333,133 B2This patent

From the US filing history. Foreign family members aren’t listed.

Timeline

Citations

Open elsewhere

Building an agent or pulling many patents? Use the API or MCP server instead of scraping pages. Get an API key