reinventing the inventory

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John is wondering..”How could I find the coffee maker my parents had when I was ten years old??..” The current merchant systems have a tendency to filter out objects that do not have a mercantile value. For example, John is searching for an object that has a value for him and maybe not for other people and for the common mercantile system. For this reason, it will be very difficult for him to find the object even on the web. On the other hand, we observe the development of second-hand shops that gather objects that are pushed aside. John knows that he could have a chance to find its coffee maker in those shops. However, he may have to visit many places to finally find it! Starting from this observation, we propose a novel approach to manage storage and cataloguing of objects of any kind. The idea consists in assisting the digitizing of objects collected by 2nd hand shops in order to allow them to publish online their catalog.

TRANSCRIPT

CécilePicard‐LimpensDr.ComputerScienceccl.picard@gmail.com

FreddyLimpensPh.DComputerSciencefreddy.limpens@inria.fr

HowwillIgetridofalltheserustycoffeemakers??

1.  Makingvisibleonthewebthestockof2ndhandshops("ressourceries",EmmauscommuniMes,SalvaMonArmy,etc.)

2.  HelpingtheseorganizaMonsdigiMzingandcataloguingtheirstock

3.  EnhancingcategorizaMonsandsearchincatalogswithsemanMctechnologies

Trainingdataclustersofobjects

associatedtoaclass

(tag)

1.Takeapicture

2.AUTOMATICshaperecogni;on:‐ Findclosestcluster‐ linktagtoobject

Hotliquidcontainer

Hotliquidcontainer

coffeemakercoffeepot

teapot =subClassOf

Seman;ctechnologiesSetofontologies

describingclassesofobjects(tags)andtheirrelaMons

id:hl‐123456tags:hotliquidcontainer☐coffeemaker coffeepot☐teapot

3.SEMI‐AUTOMATICrefiningofthetagging‐ AutomaMcallysuggestrelatedtags(ontology)‐ ManuallyvalidateorcorrectsuggesMons

Picture

AUTOMATICshaperecogni;on:‐ Findclosestcluster‐ linktagtoobject

Hotliquidcontainer

RELATEDWORK

ImageanalysistoolswithmachinelearningandstaMsMcalmodelingtechniques

•  FIRE(FlexibleImageRetrievalEngine),acontent‐basedimageretrievalsystem

ThomasDeselaers,RWTHAachenUniversity

•  LEARteam:visualobjectrecogniMonforobjectcategorydetecMon

INRIA‐LJKGrenoble

•  Mediacycle:allowstobrowseimagelibrariesbyorganizingthemintoclusterstakingintoaccountshape,colorortexture(viaopencvlibrary)UniversitédeMons&numediart,Belgium

?

?

?

Thegoal:FindingsemanMcally

RelatedtagsToenhancesearching

coffeemaker

Theidea:1./MappingtagsWithontologies’concepts

Hotliquidcontainer

coffeemakercoffeepot

teapot

=subClassOf

www.slideshare.net/fabien_gandon/web‐smanMque‐et‐web‐social‐1700977

www.slideshare.net/fabien_gandon/web‐smanMque‐et‐web‐social‐1700977

www.slideshare.net/fabien_gandon/web‐smanMque‐et‐web‐social‐1700977

Theidea:2./MiningsemanMcrelaMonsFromtags’structureandfeatures

String‐basedmapping

Coocurringtags

Resultsfor"coffeemaker":

coffeemaker

Relatedresults:

Resultsfor"teapot":

Resultsfor"coffeepot":

1. Theuserenter"coffeemaker"

2. ThesystemsuggestsaddiMonalresultsthankstosemanMcrelaMons

•  AnautomaMcarchivingofsecond‐handobjectsandtheireasyretrievingbyapotenMaluser

•  Agoodpictureofsustainabledevelopment

•  Allthetechniquesusedaimedtobefreeandopensource

•  BenchmarkcurrentshaperecogniMonmethods onourspecificproblem

•  Lookingforavailableontologies/folksonomiesofeverydayobjectstobootstrapsemanMcfuncMonnaliMes

•  PracMcalexperimentina«ressourcerie» (hnp://courtcircuioelleMn.wordpress.com/)

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