The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Mar. 05, 2002
Filed:
Jul. 13, 2000
Yanlin Guo, Lawrenceville, NJ (US);
Rakesh Kumar, Monmouth Junction, NJ (US);
Harpreet Sawhney, West Windsor Township, NJ (US);
Sarnoff Corporation, Princeton, NJ (US);
Abstract
A system and method that detects independently moving objects in 3D scenes which are viewed under camera motion progressively applies constraints to the images to ensure the stability of the constraints. The system first calculates 2D view geometry constraints for a set of images. These constraints are tested to determine if the imaged scene exhibits significant 3D characteristics. If it does, then 3D shape constraints, are applied to the set of images. The 3D shape constraints are themselves constrained by the 2D view geometry constraints. The set of images is then tested to identify areas that are inconsistent with the 2D or 3D constraints. These areas correspond to the moving objects. The 2D view geometry constraints are calculated by computing a dominant image alignment for successive pairs of images and then computing constrained epipolar transformations for the two image pairs. This 2D view geometry is further refined based on a plurality of target point correspondences among the plurality of frames. The epipolar geometry for the point correspondence having a minimum median error is selected as the 2D view geometry of the scene. The 3D shape constraint is a parallax geometry that is calculated by iteratively minimizing errors in a parametric alignment of the images using an estimated parallax geometry.