Real-Time Computer Vision
Christopher M. Brown, Demetri Terzopoulos
Cambridge University Press, Mar 30, 1995 - Computers - 232 pages
Computer vision is a rapidly developing and highly interdisciplinary field of computer science and engineering in which researchers are attempting to create vision algorithms that can analyze dynamic images at real-time rates. Real-time vision is needed for automated systems to keep pace with real-world activities and thus control or respond appropriately to them. This is the first book devoted to the subject of real-time computer vision, and it includes articles by some of the leading researchers in the world. The focus is on algorithms for interpreting visual input at video rates and on using the gathered information for decision-making and control. Topics covered include: shape recovery; model-based vehicle tracking; active exploration; tracking heads and eyes; controlling robot behavior; visual monitoring; controlling distributed robots. The book will be of interest to students, researchers and engineers involved in the design and programming of visually guided systems.
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Tracking Moving Heads
Tracking and Measuring Drivers Eyes
ModelBased Vision for Traffic Scenes Using the
Active Exploration of Dynamic and Static
Robust Shape Recovery from Occluding
Visual Robot Guidance from Uncalibrated
Control of Visually Guided Behaviors
Hybrid Problems Need Hybrid Solutions?
3D affine affine camera affine epipolar affine stereo affine transformation algorithm analysis applied approach B-spline behaviors Blake calibration chapter clusters component Computer Vision Conference on Computer constraint contour control strategy coordinates corner Corner detection correlation corresponding covariance curvature defined deformation detection discrete distance driver dynamic edge edge detection edgel epipolar curves epipolar geometry epipolar line equation error estimate feature feedback Figure finite state machine fovea frame gaze controller gripper IEEE image plane image sequences initial input Kalman filter linear Machine Vision MAST's matrix module motion moving noise object obstacle obtained optical flow orientation parallel parameters pixels planar pose position and velocity prediction problem projection real-time reconstruction region of interest robot rotation RTCV saccade scale scene Section shape structure structure from motion subspace target techniques template tion tracker tracking trajectories University of Oxford vectors vehicle visual Zisserman