Demo: Smartwatch based shopping gesture recognition

In the current retail segment, the retail store owners are keen to understand the browsing behavior and purchase pattern of the shoppers inside the physical stores. Profiling the behavior of the shopper is key to success for any marketing strategies that can optimize or personalize shopping-related s...

Full description

Saved in:
Bibliographic Details
Main Authors: RADHAKRISHNAN, Meeralakshmi, ESWARAN, Sharanya, SEN, Sougata, SUBBARAJU, Vigneshwaran, MISRA, Archan, BALAN, Rajesh Krishna
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2016
Subjects:
Online Access:https://ink.library.smu.edu.sg/sis_research/3589
https://ink.library.smu.edu.sg/context/sis_research/article/4590/viewcontent/Demo_Smartwatch_based_shopping_gesture_recognition.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Singapore Management University
Language: English
id sg-smu-ink.sis_research-4590
record_format dspace
spelling sg-smu-ink.sis_research-45902020-03-30T02:19:49Z Demo: Smartwatch based shopping gesture recognition RADHAKRISHNAN, Meeralakshmi ESWARAN, Sharanya SEN, Sougata SUBBARAJU, Vigneshwaran MISRA, Archan BALAN, Rajesh Krishna In the current retail segment, the retail store owners are keen to understand the browsing behavior and purchase pattern of the shoppers inside the physical stores. Profiling the behavior of the shopper is key to success for any marketing strategies that can optimize or personalize shopping-related services in real-time. We envision that exploiting the knowledge of real-time behavior of shopper’s in-store activities enables novel applications such as: (a) targeted advertising or recommendations: based on longer term shopper profiles, (b) proactive retail help to assist the shoppers who are confused in choosing between two items, (c) smart reminders that can remind the shoppers to pickup an item in the shopping list that they might have missed. Our work is motivated by the fact that a significant fraction of in-store shopping activities involve gestural interactions with objects of interest (such as picking up an item and putting the item in the shopping cart in a grocery store or retrieving and trying out a dress in a clothing store). In our recent works, we showed the design and initial prototype of frameworks for reliably inferring shopper’s in-store interactions and behavior by just observing their hand and foot movement inside a store. The hand gestures and locomotive pattern of the shopper inside a store is identified by appropriately mining the sensor data from shopper's personal smartphone and wearable devices (smartwatch). 2016-06-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/3589 info:doi/10.1145/2938559.2938572 https://ink.library.smu.edu.sg/context/sis_research/article/4590/viewcontent/Demo_Smartwatch_based_shopping_gesture_recognition.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Location analytics retail trade shopper behavior Software Engineering Technology and Innovation
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Location analytics
retail trade
shopper behavior
Software Engineering
Technology and Innovation
spellingShingle Location analytics
retail trade
shopper behavior
Software Engineering
Technology and Innovation
RADHAKRISHNAN, Meeralakshmi
ESWARAN, Sharanya
SEN, Sougata
SUBBARAJU, Vigneshwaran
MISRA, Archan
BALAN, Rajesh Krishna
Demo: Smartwatch based shopping gesture recognition
description In the current retail segment, the retail store owners are keen to understand the browsing behavior and purchase pattern of the shoppers inside the physical stores. Profiling the behavior of the shopper is key to success for any marketing strategies that can optimize or personalize shopping-related services in real-time. We envision that exploiting the knowledge of real-time behavior of shopper’s in-store activities enables novel applications such as: (a) targeted advertising or recommendations: based on longer term shopper profiles, (b) proactive retail help to assist the shoppers who are confused in choosing between two items, (c) smart reminders that can remind the shoppers to pickup an item in the shopping list that they might have missed. Our work is motivated by the fact that a significant fraction of in-store shopping activities involve gestural interactions with objects of interest (such as picking up an item and putting the item in the shopping cart in a grocery store or retrieving and trying out a dress in a clothing store). In our recent works, we showed the design and initial prototype of frameworks for reliably inferring shopper’s in-store interactions and behavior by just observing their hand and foot movement inside a store. The hand gestures and locomotive pattern of the shopper inside a store is identified by appropriately mining the sensor data from shopper's personal smartphone and wearable devices (smartwatch).
format text
author RADHAKRISHNAN, Meeralakshmi
ESWARAN, Sharanya
SEN, Sougata
SUBBARAJU, Vigneshwaran
MISRA, Archan
BALAN, Rajesh Krishna
author_facet RADHAKRISHNAN, Meeralakshmi
ESWARAN, Sharanya
SEN, Sougata
SUBBARAJU, Vigneshwaran
MISRA, Archan
BALAN, Rajesh Krishna
author_sort RADHAKRISHNAN, Meeralakshmi
title Demo: Smartwatch based shopping gesture recognition
title_short Demo: Smartwatch based shopping gesture recognition
title_full Demo: Smartwatch based shopping gesture recognition
title_fullStr Demo: Smartwatch based shopping gesture recognition
title_full_unstemmed Demo: Smartwatch based shopping gesture recognition
title_sort demo: smartwatch based shopping gesture recognition
publisher Institutional Knowledge at Singapore Management University
publishDate 2016
url https://ink.library.smu.edu.sg/sis_research/3589
https://ink.library.smu.edu.sg/context/sis_research/article/4590/viewcontent/Demo_Smartwatch_based_shopping_gesture_recognition.pdf
_version_ 1770573337645285376