Author: Dr Simon J. D. Prince
Edition: 1
Binding: Hardcover
ISBN: 1107011795
Publisher: Cambridge University Press
Features:
Edition: 1
Binding: Hardcover
ISBN: 1107011795
Publisher: Cambridge University Press
Features:
Computer Vision: Models, Learning, and Inference
This modern treatment of computer vision focuses on learning and inference in probabilistic models as a unifying theme. Search and download computer ebooks Computer Vision: Models, Learning, and Inference for free.
The seven-volume set comprising LNCS volumes 7572-7578 constitutes the refereed proceedings of the 12th European Conference on Computer Vision, ECCV 2012, held in Florence, Italy, in October 2012. The 408 revised papers presented were carefully reviewed and selected from 1437 submissions. The papers are organized in topical sections on geometry, 2D and 3D shapes, 3D reconstruction, visual recognition and classification, visual features and image matching, visual monitoring: action and activities, models, optimisation, learning, visual tracking and image registration, photometry: lighting and colour, and image segmentation.. Download Computer Vision computer ebooks
It shows how to use training data to learn the relationships between the observed image data and the aspects of the world that we wish to estimate, such as the 3D structure or the object class, and how to exploit these relationships to make new inferences about the world from new image data. With minimal prerequisites, the book starts from the basics of probability and model fitting and works up to real examples that the reader can implement and modify to build useful vision systems. Primarily meant for advanced undergraduate and graduate students, the detailed methodological presentation will also be useful for practitioners
Computer Vision and Action Recognition
Human action analyses and recognition are challenging problems due to large variations in human motion and appearance, camera viewpoint and environment settings. The field of action and activity representation and
recognition is relatively old, yet not well-understood by the students and research community. Some important but common motion recognition problems are even now unsolved properly by the computer vision community. However, in the last decade, a number of good approaches are proposed and evaluated subsequently by many researchers. Among those methods, some methods get significant atte
recognition is relatively old, yet not well-understood by the students and research community. Some important but common motion recognition problems are even now unsolved properly by the computer vision community. However, in the last decade, a number of good approaches are proposed and evaluated subsequently by many researchers. Among those methods, some methods get significant atte
Categories: Computer vision, Engineering inspection->Automation, Computer vision. Contributors: AD Marshall - Author. Format: Hardcover
Categories: Computer vision->Congresses. Contributors: Ales Leonardis - Editor. Format: Paperback
Categories: Computer vision. Contributors: David A. Forsyth - Author. Format: Hardcover
Computer Vision Free
It shows how to use training data to learn the relationships between the observed image data and the aspects of the world that we wish to estimate, such as the 3D structure or the object class, and how to exploit these relationships to make new inferences about the world from new image data
Primarily meant for advanced undergraduate and graduate students, the detailed methodological presentation will also be useful for practitioners
