The human face is perhaps the most familiar and easily recognized object in the world, yet both its three-dimensional shape and its two-dimensional images are complex and hard to characterize. This book develops the vocabulary of ridges and parabolic curves, of illumination eigenfaces and elastic warpings for describing the perceptually salient features of a face and its images. The book also explores the underlying mathematics and applies these mathematical techniques to the computer vision problem of face recognition, using both optical and range images.
FREE Two-Day Shipping for Students. Learn more |
Book Description
Special Offers and Product Promotions
- Buy $50 in qualifying physical textbooks, get $5 in Amazon MP3 Credit. Here's how (restrictions apply)
Frequently Bought Together
Product Details
Would you like to update product info or give feedback on images?
|
Customer Reviews
|
There are no customer reviews yet.
|
|||
|
Video reviews
|
Inside This Book
(learn more)
First Sentence:
The term "pattern theory" was introduced by Ulf Grenander in the 1970s (Grenander 76-81) as a name for a field of applied mathematics which gave a theoretical setting for a large number of related ideas, techniques and results from fields such as computer vision (D. Geman 90), speech recognition (Rabiner 90, 93), statistical pattern recognition (Ripley 96), neural nets (Hertz 91) and parts of artificial intelligence (Pearl 88). Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
hyperbolic ridge, limiting principal directions, global warp, elliptic ridge, hyperbolic cusps, rhamphoid cusp, elliptic cusps, parabolic set, umbilic points, elliptic umbilic, symmetry match, hyperbolic sectors, hyperbolic umbilics, red ridge, scalar features, ridge curves, curvature features, cubic part, elliptic region, hyperbolic region, nose ridge, symmetry set, ridge point, eye cavity, principal curvatures Key Phrases - Capitalized Phrases (CAPs): (learn more)
Modeling Variations, Finding Facial Features, Number of Coefficients, What's Next, Bayes Probability Theory, Image Data Figure, Overview of Approaches, Surface Figure New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
The term "pattern theory" was introduced by Ulf Grenander in the 1970s (Grenander 76-81) as a name for a field of applied mathematics which gave a theoretical setting for a large number of related ideas, techniques and results from fields such as computer vision (D. Geman 90), speech recognition (Rabiner 90, 93), statistical pattern recognition (Ripley 96), neural nets (Hertz 91) and parts of artificial intelligence (Pearl 88). Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
hyperbolic ridge, limiting principal directions, global warp, elliptic ridge, hyperbolic cusps, rhamphoid cusp, elliptic cusps, parabolic set, umbilic points, elliptic umbilic, symmetry match, hyperbolic sectors, hyperbolic umbilics, red ridge, scalar features, ridge curves, curvature features, cubic part, elliptic region, hyperbolic region, nose ridge, symmetry set, ridge point, eye cavity, principal curvatures Key Phrases - Capitalized Phrases (CAPs): (learn more)
Modeling Variations, Finding Facial Features, Number of Coefficients, What's Next, Bayes Probability Theory, Image Data Figure, Overview of Approaches, Surface Figure New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Citations (learn more)
This book cites 29
books:
See all 29 books this book cites
1
book
cites this book:
- Neural Networks (Quantitative Applications in the Social Sciences) by Hervé Abdi in Back Matter (1), and Back Matter (2)
- Solid Shape (Artificial Intelligence) by Jan J. Koenderink in Back Matter
- Sensory Communication by Walter A. Rosenblith in Back Matter
- Emotion in the Human Face (Studies in Emotion and Social Interaction) by Paul Ekman in Back Matter
- Pattern Recognition and Neural Networks by Brian D. Ripley in Back Matter
See all 29 books this book cites
- Pattern Recognition From Classical to Modern Approaches by Sankar K. Pal on page 164
Books on Related Topics
(learn more)
|
Tags Customers Associate with This Product(What's this?)Click on a tag to find related items, discussions, and people.
|
Sell a Digital Version of This Book in the Kindle Store
If you are a publisher or author and hold the digital rights to a book, you can sell a digital version of it in our Kindle Store.
Learn more
Customer Discussions
|
This product's forum
Active discussions in related forums
Search Customer Discussions
|
Related forums
|
Listmania!
So You'd Like to...
Look for Similar Items by Category
- Books > Computers & Technology > Computer Science > Artificial Intelligence > Computer Vision
- Books > Computers & Technology > Graphic Design > Printing
- Books > Computers & Technology > Programming > Algorithms
- Books > Computers & Technology > Programming > Graphics & Multimedia
- Books > Computers & Technology > Software
- Books > Computers & Technology > Web Development
- Books > New & Used Textbooks > Computer Science > Graphics & Visualization
- Books > New & Used Textbooks > Science & Mathematics > Mathematics
- Books > Science & Math > Mathematics
- Books > Science & Math > Physics > Optics
