Picture 1 of 1
Picture 1 of 1
Machine Learning Techniques for Gait Biometric Recognition: Using the Ground Rea
US $65.99
ApproximatelyEUR 59.22
Condition:
New
A new, unread, unused book in perfect condition with no missing or damaged pages. See the seller's listing for full details.
3 available
Postage:
Free Economy Shipping.
Located in: Fairfield, Ohio, United States
Delivery:
Estimated between Fri, 4 Oct and Thu, 10 Oct to 43230
Returns:
30 days return. Buyer pays for return postage.
Payments:
Shop with confidence
Seller assumes all responsibility for this listing.
eBay item number:364699155877
Item specifics
- Condition
- ISBN-13
- 9783319804866
- Type
- NA
- Publication Name
- NA
- ISBN
- 9783319804866
- Book Title
- Machine Learning Techniques for Gait Biometric Recognition : Using the Ground Reaction Force
- Publisher
- Springer International Publishing A&G
- Item Length
- 9.2 in
- Publication Year
- 2018
- Format
- Trade Paperback
- Language
- English
- Illustrator
- Yes
- Item Height
- 0.6 in
- Genre
- Computers, Technology & Engineering, Science
- Topic
- Signals & Signal Processing, Computer Vision & Pattern Recognition, Physics / General
- Item Weight
- 16 Oz
- Item Width
- 6.1 in
- Number of Pages
- Xxxiv, 223 Pages
About this product
Product Identifiers
Publisher
Springer International Publishing A&G
ISBN-10
3319804863
ISBN-13
9783319804866
eBay Product ID (ePID)
21038543946
Product Key Features
Book Title
Machine Learning Techniques for Gait Biometric Recognition : Using the Ground Reaction Force
Number of Pages
Xxxiv, 223 Pages
Language
English
Publication Year
2018
Topic
Signals & Signal Processing, Computer Vision & Pattern Recognition, Physics / General
Illustrator
Yes
Genre
Computers, Technology & Engineering, Science
Format
Trade Paperback
Dimensions
Item Height
0.6 in
Item Weight
16 Oz
Item Length
9.2 in
Item Width
6.1 in
Additional Product Features
Intended Audience
Trade
Number of Volumes
1 vol.
Table Of Content
Introduction.- Background.- Experimental Design and Dataset.- Feature Extraction.-Normalization.- Classification.- Measured Performance.- Experimental Analysis.- Conclusion.
Synopsis
This book focuses on how machine learning techniques can be used to analyze and make use of one particular category of behavioral biometrics known as the gait biometric. A comprehensive Ground Reaction Force (GRF)-based Gait Biometrics Recognition framework is proposed and validated by experiments. In addition, an in-depth analysis of existing recognition techniques that are best suited for performing footstep GRF-based person recognition is also proposed, as well as a comparison of feature extractors, normalizers, and classifiers configurations that were never directly compared with one another in any previous GRF recognition research. Finally, a detailed theoretical overview of many existing machine learning techniques is presented, leading to a proposal of two novel data processing techniques developed specifically for the purpose of gait biometric recognition using GRF. This book · introduces novel machine-learning-based temporal normalization techniques · bridges research gaps concerning the effect of footwear and stepping speed on footstep GRF-based person recognition · provides detailed discussions of key research challenges and open research issues in gait biometrics recognition · compares biometrics systems trained and tested with the same footwear against those trained and tested with different footwear, Introduction.- Background.- Experimental Design and Dataset.- Feature Extraction.-Normalization.- Classification.- Measured Performance.- Experimental Analysis.- Conclusion., This book focuses on how machine learning techniques can be used to analyze and make use of one particular category of behavioral biometrics known as the gait biometric. A comprehensive Ground Reaction Force (GRF)-based Gait Biometrics Recognition framework is proposed and validated by experiments. In addition, an in-depth analysis of existing recognition techniques that are best suited for performing footstep GRF-based person recognition is also proposed, as well as a comparison of feature extractors, normalizers, and classifiers configurations that were never directly compared with one another in any previous GRF recognition research. Finally, a detailed theoretical overview of many existing machine learning techniques is presented, leading to a proposal of two novel data processing techniques developed specifically for the purpose of gait biometric recognition using GRF. This book - introduces novel machine-learning-based temporal normalization techniques - bridges research gaps concerning the effect of footwear and stepping speed on footstep GRF-based person recognition - provides detailed discussions of key research challenges and open research issues in gait biometrics recognition - compares biometrics systems trained and tested with the same footwear against those trained and tested with different footwear
LC Classification Number
TK5102.9
Item description from the seller
Business seller information
Premier Books LLC
David Taylor
26C Trolley Sq
19806-3356 Wilmington, DE
United States
I certify that all my selling activities will comply with all EU laws and regulations.
Popular categories from this shop
Registered as a business seller
Seller Feedback (1,032,469)
- t***n (125)- Feedback left by buyer.Past monthVerified purchaseThis book base been received thank you
- n***2 (49)- Feedback left by buyer.Past monthVerified purchaseVery happy! Thank you so much- would purchase from this seller again
- g***g (84)- Feedback left by buyer.Past monthVerified purchase👍
More to explore:
- Guitar Techniques Magazines,
- Guitar Techniques August Magazines,
- December Guitar Techniques Magazines,
- Guitar Techniques Magazines in English,
- Management Techniques Books,
- Look and Learn Magazines,
- Workbook Adult Learning & University Books,
- Biology Adult Learning & University Books,
- Law Adult Learning & University Textbook,
- Anatomy Adult Learning & University Books