Available:*
Library | Item Barcode | Call Number | Material Type | Item Category 1 | Status |
|---|---|---|---|---|---|
Searching... | 30000002547796 | TA1632 A39 1992 | Open Access Book | Book | Searching... |
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Summary
Summary
Active Vision explores important themes emerging from the active vision paradigm, which has only recently become an established area of machine vision. In four parts the contributions look in turn at tracking, control of vision heads, geometric and task planning, and architectures and applications, presenting research that marks a turning point for both the tasks and the processes of computer vision. The eighteen chapters in Active Vision draw on traditional work in computer vision over the last two decades, particularly in the use of concepts of geometrical modeling and optical flow; however, they also concentrate on relatively new areas such as control theory, recursive statistical filtering, and dynamical modeling. Active Vision documents a change in emphasis, one that is based on the premise that an observer (human or computer) may be able to understand a visual environment more effectively and efficiently if the sensor interacts with that environment, moving through and around it, culling information selectively, and analyzing visual sensory data purposefully in order to answer specific queries posed by the observer. This method is in marked contrast to the more conventional, passive approach to computer vision where the camera is supposed to take in the whole scene, attempting to make sense of all that it sees.
Reviews 1
Choice Review
Over the past 30 years, the field of computer vision has grown and evolved greatly. An important subarea today is "active vision," the combination of controlled motion and visual perception. A computer-controlled camera, that can pan, tilt, focus, and/or move toward the subject on a robotic arm, is a key element of an active vision system. The combination of robots and vision will be increasingly important as the technology is applied to problems in manufacturing, transportation, and other areas. This book collects together recent papers by eminent researchers in active vision who present a broad view of research efforts. Included are visual tracking using snakes and deformable templates, control of vision heads, binocular stereo vergence control, motion planning and navigation using vision, and automatic vehicle-driving systems. The writing is generally clear, and the papers are well illustrated with diagrams and photographs. However, a reader will need an undergraduate mathematics background to understand these papers. The material is most suited to researchers and graduate students in robotics, electrical engineering, mechanical engineering, and computer science. S. L. Tanimoto; University of Washington
