EconPapers    
Economics at your fingertips  
 

Hausdorff Path Clustering and Hidden Markov Model Applied to Person Movement Prediction in Retail Spaces

Francisco Romaldo Mendes ()
Additional contact information
Francisco Romaldo Mendes: Deloitte Consulting LLP

A chapter in Advances in Analytics and Applications, 2019, pp 67-76 from Springer

Abstract: Abstract Current advances in technology allow for the efficient capturing and storage of high-resolution and high-frequency person movement data.

Keywords: Personal Movement; Path Clustering; Hidden Markov Models; Ramer Douglas Peucker (RDP); Grand Ballroom (search for similar items in EconPapers)
Date: 2019
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-981-13-1208-3_7

Ordering information: This item can be ordered from
http://www.springer.com/9789811312083

DOI: 10.1007/978-981-13-1208-3_7

Access Statistics for this chapter

More chapters in Springer Proceedings in Business and Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-04-13
Handle: RePEc:spr:prbchp:978-981-13-1208-3_7