000 -LEADER |
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03132nam a22004215i 4500 |
003 - CONTROL NUMBER IDENTIFIER |
control field |
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005 - DATE AND TIME OF LATEST TRANSACTION |
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20140310143344.0 |
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
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cr nn 008mamaa |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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100715s2010 gw | s |||| 0|eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
International Standard Book Number |
9783642136429 |
|
978-3-642-13642-9 |
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
Classification number |
629.892 |
Edition number |
23 |
264 #1 - |
-- |
Berlin, Heidelberg : |
-- |
Springer Berlin Heidelberg, |
-- |
2010. |
912 ## - |
-- |
ZDB-2-ENG |
100 1# - MAIN ENTRY--PERSONAL NAME |
Personal name |
Govea, Alejandro Dizan Vasquez. |
Relator term |
author. |
245 10 - IMMEDIATE SOURCE OF ACQUISITION NOTE |
Title |
Incremental Learning for Motion Prediction of Pedestrians and Vehicles |
Medium |
[electronic resource] / |
Statement of responsibility, etc |
by Alejandro Dizan Vasquez Govea. |
300 ## - PHYSICAL DESCRIPTION |
Extent |
160p. 35 illus. in color. |
Other physical details |
online resource. |
440 1# - SERIES STATEMENT/ADDED ENTRY--TITLE |
Title |
Springer Tracts in Advanced Robotics, |
International Standard Serial Number |
1610-7438 ; |
Volume number/sequential designation |
64 |
505 0# - FORMATTED CONTENTS NOTE |
Formatted contents note |
I: Background -- Probabilistic Models -- II: State of the Art -- Intentional Motion Prediction -- Hidden Markov Models -- III: Proposed Approach -- Growing Hidden Markov Models -- Learning and Predicting Motion with GHMMs -- IV: Experiments -- Experimental Data -- Experimental Results -- V: Conclusion -- Conclusions and Future Work. |
520 ## - SUMMARY, ETC. |
Summary, etc |
Modeling and predicting human and vehicle motion is an active research domain. Owing to the difficulty in modeling the various factors that determine motion (e.g. internal state, perception) this is often tackled by applying machine learning techniques to build a statistical model, using as input a collection of trajectories gathered through a sensor (e.g. camera, laser scanner), and then using that model to predict further motion. Unfortunately, most current techniques use offline learning algorithms, meaning that they are not able to learn new motion patterns once the learning stage has finished. This books presents a lifelong learning approach where motion patterns can be learned incrementally, and in parallel with prediction. The approach is based on a novel extension to hidden Markov models, and the main contribution presented in this book, called growing hidden Markov models, which gives us the ability to learn incrementally both the parameters and the structure of the model. The proposed approach has been extensively validated with synthetic and real trajectory data. In our experiments our approach consistently learned motion models that were more compact and accurate than those produced by two other state-of-the-art techniques, confirming the viability of lifelong learning approaches to build human behavior models. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Engineering. |
|
Topical term or geographic name as entry element |
Artificial intelligence. |
|
Topical term or geographic name as entry element |
Optical pattern recognition. |
|
Topical term or geographic name as entry element |
Engineering. |
|
Topical term or geographic name as entry element |
Robotics and Automation. |
|
Topical term or geographic name as entry element |
Artificial Intelligence (incl. Robotics). |
|
Topical term or geographic name as entry element |
Pattern Recognition. |
710 2# - ADDED ENTRY--CORPORATE NAME |
Corporate name or jurisdiction name as entry element |
SpringerLink (Online service) |
773 0# - HOST ITEM ENTRY |
Title |
Springer eBooks |
776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
Display text |
Printed edition: |
International Standard Book Number |
9783642136412 |
856 40 - ELECTRONIC LOCATION AND ACCESS |
Uniform Resource Identifier |
http://dx.doi.org/10.1007/978-3-642-13642-9 |
942 ## - ADDED ENTRY ELEMENTS (KOHA) |
Source of classification or shelving scheme |
|
Item type |
E-Book |