Ebook: Integrating Graphics and Vision for Object Recognition

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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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.

---

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.
Content:
Front Matter....Pages i-xi
Introduction....Pages 1-9
Previous Work....Pages 11-32
Render: Predicting Scenes....Pages 33-55
Match: Comparing Images....Pages 57-96
Refine: Iterative Search....Pages 97-129
Evaluation....Pages 131-151
Conclusions....Pages 153-156
Back Matter....Pages 157-184

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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.
Content:
Front Matter....Pages i-xi
Introduction....Pages 1-9
Previous Work....Pages 11-32
Render: Predicting Scenes....Pages 33-55
Match: Comparing Images....Pages 57-96
Refine: Iterative Search....Pages 97-129
Evaluation....Pages 131-151
Conclusions....Pages 153-156
Back Matter....Pages 157-184
....