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140122 ||| eng |
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|a 9781475755244
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|a Stevens, Mark R.
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|a Integrating Graphics and Vision for Object Recognition
|h Elektronische Ressource
|c by Mark R. Stevens, J. Ross Beveridge
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| 250 |
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|a 1st ed. 2001
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| 260 |
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|a New York, NY
|b Springer US
|c 2001, 2001
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| 300 |
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|a XII, 184 p
|b online resource
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|a 1. Introduction -- 2. Previous Work -- 3. Render: Predicting Scenes -- 4. Match: Comparing Images -- 5. Refine: Iterative Search -- 6. Evaluation -- 7. Conclusions -- Appendices -- A— Generating Scene Hypotheses -- 1. Object Detection and Pose Indexing -- 2. Detection based on Color Decision Trees -- 3. Pose Indexing
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| 653 |
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|a Computer graphics
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| 653 |
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|a Image processing / Digital techniques
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| 653 |
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|a Control, Robotics, Automation
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| 653 |
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|a Computer vision
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| 653 |
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|a Computer Graphics
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| 653 |
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|a Artificial Intelligence
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| 653 |
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|a Computer Vision
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| 653 |
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|a Computer Imaging, Vision, Pattern Recognition and Graphics
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| 653 |
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|a Control engineering
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| 653 |
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|a Artificial intelligence
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| 653 |
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|a Robotics
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| 653 |
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|a Automation
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| 700 |
1 |
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|a Beveridge, J. Ross
|e [author]
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| 041 |
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7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b SBA
|a Springer Book Archives -2004
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| 490 |
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|a The Springer International Series in Engineering and Computer Science
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| 028 |
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|a 10.1007/978-1-4757-5524-4
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| 856 |
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|u https://doi.org/10.1007/978-1-4757-5524-4?nosfx=y
|x Verlag
|3 Volltext
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|a 006
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| 520 |
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|a Integrating Graphics and Vision for Object Recognition serves as a reference for electrical engineers and computer scientists researching computer vision or computer graphics. Computer graphics and computer vision can be viewed as different sides of the same coin. In graphics, algorithms are given knowledge about the world in the form of models, cameras, lighting, etc., and infer (or render) an image of a scene. In vision, the process is the exact opposite: algorithms are presented with an image, and infer (or interpret) the configuration of the world. This work focuses on using computer graphics to interpret camera images: using iterative rendering to predict what should be visible by the camera and then testing and refining that hypothesis. Features of the book include: Many illustrations to supplement the text; A novel approach to the integration of graphics and vision; Genetic algorithms for vision; Innovations in closed loop object recognition. Integrating Graphics and Vision for Object Recognition will be of interest to research scientists and practitioners working in fields related to the topic. It may also be used as an advanced-level graduate text
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