Closed form solutions to image flow equations for planar surfaces in motion
Computer Vision, Graphics, and Image Processing
Object recognition using oriented model points
Computer Vision, Graphics, and Image Processing
Structure and motion from optical flow under orthographic projection
Computer Vision, Graphics, and Image Processing
Structure and motion from optical flow under perspective projection
Computer Vision, Graphics, and Image Processing
Camera rotation invariance of image characteristics
Computer Vision, Graphics, and Image Processing
Constraints on length and angle
Computer Vision, Graphics, and Image Processing
VITS-A Vision System for Autonomous Land Vehicle Navigation
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special Issue on Industrial Machine Vision and Computer Vision Technology:8MPart
Vision and navigation for the Carnegie-Mellon navlab
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special Issue on Industrial Machine Vision and Computer Vision Technology:8MPart
Transformation of Optical Flow by Camera Rotation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Vision: A Computational Investigation into the Human Representation and Processing of Visual Information
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Methods of 3D recovery in computer vision for computing the shape and motion of an object from projected images when an object model is available are classified into two types: the 3D Euclidean approach, which is based on geometrical constraints in 3D Euclidean space, and the 2D non-Euclidean space. Implications of these two approaches are discussed, and some illustrating examples are presented.