KEYWORDS: Cameras, Video, Video surveillance, 3D image processing, 3D modeling, Computer simulations, Image processing, Video processing, Photography, Systems modeling
Under National Ground Intelligence Center (NGIC) sponsorship, BBN Technologies (BBN) has developed a physical model and a software utility to estimate the range and orientation of a target from video images and known geometric information about the target. This capability can be used in conjunction with law enforcement sensor systems to enhance situation assessment and facilitate the associated decisions process. The target range and orientation estimation system (Video Range Finder) allows the user to associate identifiable features of the video image with physical components of the target through an interactive process. The three-dimensional polyhedron defined by the location of these components in the coordinate frame of the target, is projected along the viewing axis onto a two-dimensional polygonal image at the focal plane of the video camera. The azimuth, elevation, and viewing-axis rotation angles are obtained by solving numerically the associated non-linear projection equations. The calculated angles are subsequently used in the estimation of the target range. The paper discusses the solution method and demonstrates the application of the system using both simulated and real objects.
Under National Ground Intelligence Center (NGIC) sponsorship, BBN Technologies (BBN) has developed a physical model and a software system to estimate the range and orientation of a target from video images and known information about the target and video camera. This capability may be exploited in an unattended ground sensors field to enhance situation assessment for subsequent response decisions. The target range and orientation estimation system (Video Range Finder) is based on an interactive procedure enabling the user to associate identifiable features of the video image with physical components of the target. These points define a three-dimensional polyhedron in the coordinate frame of the target, which is projected onto the two-dimensional polygon image at the focal plane of the video camera. The associated projection equations are non-linear with respect to the azimuth, elevation, and viewing-axis rotation angles of the video camera, therefore, a solution for these angles is obtained numerically. The calculated angles are subsequently used in the estimation of the target range. The paper discusses the physical model, describes the algorithm for estimating target range and orientation, and demonstrates its application using both simulated and real objects.
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