Video Mining,
2000
WWW Link.
Vendor, Surveillance. Primary market is market analysis (i.e. tracking shoppers in a store to
analyze shopping patterns).
Conrad, G.L.[Gary L.],
Denenberg, B.A.[Byron A.],
Kramerich, G.L.[George L.],
Video traffic monitor for retail establishments and the like,
US_Patent5,465,115, Nov 7, 1995
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BibRef
9511
Popa, M.C.[Mirela C.],
Rothkrantz, L.J.M.[Leon J.M.],
Shan, C.F.[Cai-Feng],
Gritti, T.[Tommaso],
Wiggers, P.,
Semantic assessment of shopping behavior using trajectories, shopping
related actions, and context information,
PRL(34), No. 7, 1 May 2013, pp. 809-819.
Elsevier DOI
1303
BibRef
Earlier: A1, A4, A2, A3, A5:
Detecting Customers' Buying Events on a Real-Life Database,
CAIP11(I: 17-25).
Springer DOI
1109
Shopping behavior; Semantic analysis; Trajectory analysis; Action
recognition; Hidden Markov Models
BibRef
Popa, M.C.,
Rothkrantz, L.J.M.,
Shan, C.,
Wiggers, P.,
Assessment of customers' level of interest,
ICIP12(41-44).
IEEE DOI
1302
BibRef
Popa, M.C.,
Rothkrantz, L.J.M.,
Wiggers, P.,
Shan, C.,
Shopping behavior recognition using a language modeling analogy,
PRL(34), No. 15, 2013, pp. 1879-1889.
Elsevier DOI
1309
Shopping behavior
BibRef
Ahn, H.I.[Hyung-Il],
Picard, R.W.,
Measuring Affective-Cognitive Experience and Predicting Market
Success,
AffCom(5), No. 2, April 2014, pp. 173-186.
IEEE DOI
1411
cognition
BibRef
Popa, M.C.[Mirela Carmia],
Multimodal Assessment of Shopping Behavior,
ELCVIA(14), No. 3, 2015, pp. xx-yy.
DOI Link
1601
Thesis summary.
BibRef
Liu, S.[Song],
Li, W.Q.[Wan-Qing],
Davis, S.[Stephen],
Ritz, C.[Christian],
Tian, H.[Hongda],
Planogram Compliance Checking Based on Detection of Recurring
Patterns,
MultMedMag(23), No. 2, April 2016, pp. 54-63.
IEEE DOI
1605
Companies. Retail store layout analysis.
BibRef
Pereira, E.M.[Eduardo Marques],
Cardoso, J.S.[Jaime S.],
Morla, R.[Ricardo],
Long-range trajectories from global and local motion representations,
JVCIR(40, Part A), No. 1, 2016, pp. 265-287.
Elsevier DOI
1609
BibRef
Earlier:
Motion Flow Tracking in Unconstrained Videos for Retail Scenario,
IbPRIA13(340-349).
Springer DOI
1307
Long trajectories
BibRef
Quintana, M.,
Menendez, J.M.,
Alvarez, F.,
Lopez, J.P.,
Improving retail efficiency through sensing technologies: A survey,
PRL(81), No. 1, 2016, pp. 3-10.
Elsevier DOI
1609
Survey, Retail. Intelligent retail
BibRef
Merad, D.[Djamal],
Aziz, K.E.[Kheir-Eddine],
Iguernaissi, R.[Rabah],
Fertil, B.[Bernard],
Drap, P.[Pierre],
Tracking multiple persons under partial and global occlusions:
Application to customers' behavior analysis,
PRL(81), No. 1, 2016, pp. 11-20.
Elsevier DOI
1609
Multiple-people tracking
See also People's Re-identification Across Multiple Non-overlapping Cameras by Local Discriminative Patch Matching.
BibRef
Merad, D.[Djamal],
Drap, P.[Pierre],
Lufimpu-Luviya, Y.[Yannick],
Iguernaissi, R.[Rabah],
Fertil, B.[Bernard],
Purchase behavior analysis through gaze and gesture observation,
PRL(81), No. 1, 2016, pp. 21-29.
Elsevier DOI
1609
Purchase behavior
BibRef
Sturari, M.[Mirco],
Liciotti, D.[Daniele],
Pierdicca, R.[Roberto],
Frontoni, E.[Emanuele],
Mancini, A.[Adriano],
Contigiani, M.[Marco],
Zingaretti, P.[Primo],
Robust and affordable retail customer profiling by vision and radio
beacon sensor fusion,
PRL(81), No. 1, 2016, pp. 30-40.
Elsevier DOI
1609
Sensor fusion
BibRef
Ananthanarayanan, G.,
Bahl, P.,
Bodík, P.,
Chintalapudi, K.,
Philipose, M.,
Ravindranath, L.,
Sinha, S.,
Real-Time Video Analytics: The Killer App for Edge Computing,
Computer(50), No. 10, 2017, pp. 58-67.
IEEE DOI
1710
cloud computing, software architecture, video signal processing,
edge computing, geographically distributed architecture,
real-time video analytics, Automobiles, Bandwidth, Cameras,
Cloud computing, Streaming media, Surveillance, Video analytics,
BibRef
Ji, C.B.[Cui-Bin],
Duan, G.J.[Gui-Jiang],
Ma, H.Y.[Han-Yong],
Zhang, L.[Long],
Xu, H.Y.[Huan-Yun],
Modeling of image, video and text fusion quality data packet system
for aerospace complex products based on business intelligence,
JVCIR(59), 2019, pp. 439-447.
Elsevier DOI
1903
Balanced scorecard, Business intelligence, Data warehouse,
Quality data package, Polymorphic data, Complex product
BibRef
Santra, B.[Bikash],
Mukherjee, D.P.[Dipti Prasad],
A comprehensive survey on computer vision based approaches for
automatic identification of products in retail store,
IVC(86), 2019, pp. 45-63.
Elsevier DOI
1906
Survey, Product detection, Product recognition,
Planogram compliance, Multiple object detection, Out-of-stock detection
BibRef
Adan, A.[Antonio],
de la Rubia, D.[David],
Reconstruction of As-is Semantic 3D Models of Unorganised Storehouses,
3DV19(367-375)
IEEE DOI
1911
Image color analysis, Solid modeling,
Semantics, IEEE merchandise, Classification algorithms, Monitoring, Object recognition
BibRef
Zhao, L.,
Yao, J.,
Du, H.,
Zhao, J.,
Zhang, R.,
A Unified Object Detection Framework for Intelligent Retail Container
Commodities,
ICIP19(3891-3895)
IEEE DOI
1910
Intelligent retail, object detection, non-maximum suppression
BibRef
de Souza Junior, N.F.[Nelson Forte],
da Silva, L.A.[Leandro Augusto],
Marengoni, M.[Mauricio],
Product Recommendation Through Real-Time Object Recognition on Image
Classifiers,
ICIAR19(II:40-51).
Springer DOI
1909
BibRef
Allegrino, F.[Fioravante],
Gabellini, P.[Patrizia],
di Bello, L.[Luigi],
Contigiani, M.[Marco],
Placidi, V.[Valerio],
The Vending Shopper Science Lab: Deep Learning for Consumer Research,
NTIAP19(307-317).
Springer DOI
1909
BibRef
Paolanti, M.[Marina],
Pierdicca, R.[Roberto],
Martini, M.[Massimo],
Di Stefano, F.[Francesco],
Morbidoni, C.[Christian],
Mancini, A.[Adriano],
Malinverni, E.S.[Eva Savina],
Frontoni, E.[Emanuele],
Zingaretti, P.[Primo],
Semantic 3D Object Maps for Everyday Robotic Retail Inspection,
NTIAP19(263-274).
Springer DOI
1909
BibRef
Porta, S.L.[Salvatore La],
Marconi, F.[Fabrizio],
Lazzini, I.[Isabella],
Collecting Retail Data Using a Deep Learning Identification Experience,
NTIAP19(275-284).
Springer DOI
1909
BibRef
Gabellini, P.[Patrizia],
D'Aloisio, M.[Mauro],
Fabiani, M.[Matteo],
Placidi, V.[Valerio],
A Large Scale Trajectory Dataset for Shopper Behaviour Understanding,
NTIAP19(285-295).
Springer DOI
1909
BibRef
Klasson, M.,
Zhang, C.,
Kjellström, H.,
A Hierarchical Grocery Store Image Dataset With Visual and Semantic
Labels,
WACV19(491-500)
IEEE DOI
1904
convolutional neural nets, electronic commerce, handicapped aids,
image classification, learning (artificial intelligence),
Computer vision
BibRef
Gonzalves Vieira, M.,
Moreira, J.,
Classification of E-Commerce-Related Images Using Hierarchical
Classification with Deep Neural Networks,
WVC17(114-119)
IEEE DOI
1804
electronic commerce, image classification, neural nets,
Hierarchical Classification, Hierarchical Classifier,
image classification
BibRef
Torcinovich, A.[Alessandro],
Fratton, M.[Marco],
Pelillo, M.[Marcello],
Pravato, A.[Alberto],
Roncato, A.[Alessandro],
A Computer Vision System for Monitoring Ice-Cream Freezers,
CIAP17(II:333-342).
Springer DOI
1711
Track how much is there, sales, etc.
BibRef
Aksah, S.[Saliza],
Taslim, J.[Jamaliah],
Aziz, M.A.[Maslina Abdul],
Hamzah, P.[Paezah],
Manaf, N.A.[Norehan Abdul],
Nasruddin, Z.A.[Zan Azma],
Understanding the Atmospheric Cues Effects on Consumer Emotions:
A Case Study on Lazada Malaysia,
IVIC17(423-432).
Springer DOI
1711
BibRef
Yamamoto, J.,
Inoue, K.,
Yoshioka, M.,
Investigation of Customer Behavior Analysis Based on Top-View Depth
Camera,
HAAHDC17(67-74)
IEEE DOI
1609
behavioural sciences computing, cameras, computer vision,
consumer behaviour, feature extraction, support vector machines,
PSA based features, SVM, book store situation, computer vision,
customer behavior analysis, depth information,
human behavior analysis, pattern recognition,
pixel state analysis, support vector machines,
surveillance camera, top-view depth camera, Cameras,
Computer vision, Estimation, Feature extraction, Security,
Support vector machines, Surveillance
BibRef
Song, Y.,
Xue, Y.,
Li, C.,
Zhao, X.,
Liu, S.,
Zhuo, X.,
Zhang, K.,
Yan, B.,
Ning, X.,
Wang, Y.,
Feng, X.,
Online Cost Efficient Customer Recognition System for Retail
Analytics,
SoftBio17(9-16)
IEEE DOI
1609
cloud computing, computer vision, consumer behaviour,
feature extraction, image recognition,
learning (artificial intelligence), neural nets,
object detection, object tracking, purchasing,
retail data processing, age estimation, business strategy,
chain stores, change sales strategy, client management,
cloud computing resources, computer vision,
customer behavior data procurement, customer detection,
deep learning, feature extraction, fully automated system,
gender estimation, local computation resources,
online cost efficient customer recognition system,
purchase information collection,
real-time customer analytic system, retail business, Cameras,
Computational modeling, Estimation, Face, Feature extraction, Target, tracking
BibRef
Yashima, T.[Takuya],
Okazaki, N.[Naoaki],
Inui, K.[Kentaro],
Yamaguchi, K.[Kota],
Okatani, T.[Takayuki],
Learning to Describe E-Commerce Images from Noisy Online Data,
ACCV16(V: 85-100).
Springer DOI
1704
BibRef
Santarcangelo, V.[Vito],
Farinella, G.M.[Giovanni Maria],
Battiato, S.[Sebastiano],
Egocentric Vision for Visual Market Basket Analysis,
Egocentric16(I: 518-531).
Springer DOI
1611
BibRef
Saran, A.[Anurag],
Hassan, E.[Ehtesham],
Maurya, A.K.[Avinash Kumar],
Robust visual analysis for planogram compliance problem,
MVA15(576-579)
IEEE DOI
1507
Accuracy. Retail store shelf inspection.
BibRef
Aryafar, K.[Kamelia],
Lynch, C.[Corey],
Attenberg, J.[Josh],
Exploring User Behaviour on Etsy through Dominant Colors,
ICPR14(1437-1442)
IEEE DOI
1412
Entropy
BibRef
Ravnik, R.[Robert],
Solina, F.[Franc],
Zabkar, V.[Vesna],
Modelling In-Store Consumer Behaviour Using Machine Learning and
Digital Signage Audience Measurement Data,
VAAM14(123-133).
Springer DOI
1411
BibRef
Testori, M.[Matteo],
The Applications of Video Analytics in Media Planning, Trade and
Shopper Marketing,
VAAM14(3-20).
Springer DOI
1411
BibRef
Mäkelä, S.M.[Satu-Marja],
Järvinen, S.[Sari],
Keränen, T.[Tommi],
Lindholm, M.[Mikko],
Vildjiounaite, E.[Elena],
Shopper Behaviour Analysis Based on 3D Situation Awareness Information,
VAAM14(134-145).
Springer DOI
1411
BibRef
Pane, C.[Carlo],
Gasparini, M.[Marco],
Prati, A.[Andrea],
Gualdi, G.[Giovanni],
Cucchiara, R.[Rita],
A people counting system for business analytics,
AVSS13(135-140)
IEEE DOI
1311
Accuracy
BibRef
Carullo, M.[Mariarosaria],
Cavaliere, G.[Gianluca],
Stock Control through Video Surveillance in Logistics,
CIAP13(II:740-748).
Springer DOI
1309
BibRef
Liciotti, D.[Daniele],
Contigiani, M.[Marco],
Frontoni, E.[Emanuele],
Mancini, A.[Adriano],
Zingaretti, P.[Primo],
Placidi, V.[Valerio],
Shopper Analytics: A Customer Activity Recognition System Using a
Distributed RGB-D Camera Network,
VAAM14(146-157).
Springer DOI
1411
BibRef
Frontoni, E.[Emanuele],
Raspa, P.[Paolo],
Mancini, A.[Adriano],
Zingaretti, P.[Primo],
Placidi, V.[Valerio],
Customers' Activity Recognition in Intelligent Retail Environments,
SBA13(509-516).
Springer DOI
1309
BibRef
Trinh, H.[Hoang],
Fan, Q.F.[Quan-Fu],
Gabbur, P.[Prasad],
Pankanti, S.[Sharath],
Hand tracking by binary quadratic programming and its application to
retail activity recognition,
CVPR12(1902-1909).
IEEE DOI
1208
BibRef
Trinh, H.[Hoang],
Pankanti, S.[Sharath],
Fan, Q.F.[Quan-Fu],
Multimodal ranking for non-compliance detection in retail surveillance,
WACV12(241-246).
IEEE DOI
1203
BibRef
Bobbitt, R.[Russell],
Connell, J.[Jonathan],
Haas, N.[Norman],
Otto, C.[Charles],
Pankanti, S.[Sharath],
Payne, J.[Jason],
Visual item verification for fraud prevention in retail self-checkout,
WACV11(585-590).
IEEE DOI
1101
Self checkout systems. Augment weight with visual check.
BibRef
Pan, J.Y.[Ji-Yan],
Fan, Q.F.[Quan-Fu],
Pankanti, S.[Sharath],
Trinh, H.[Hoang],
Gabbur, P.[Prasad],
Miyazawa, S.[Sachiko],
Soft margin keyframe comparison: Enhancing precision of fraud detection
in retail surveillance,
WACV11(549-556).
IEEE DOI
1101
BibRef
Park, U.S.[Un-Sang],
Otto, C.A.,
Pankanti, S.,
Cart Auditor: A Compliance and Training Tool for Cashiers at Checkout,
PSIVT10(151-155).
IEEE DOI
1011
BibRef
Onishi, M.[Masaki],
Yoda, I.[Ikushi],
Visualization of Customer Flow in an Office Complex over a Long Period,
ICPR10(1747-1750).
IEEE DOI
1008
BibRef
Senior, A.W.,
Brown, L.,
Hampapur, A.,
Shu, C.F.,
Zhai, Y.,
Feris, R.S.,
Tian, Y.L.,
Borger, S.,
Carlson, C.,
Video analytics for retail,
AVSBS07(423-428).
IEEE DOI
0709
BibRef
Leykin, A.[Alex],
Tuceryan, M.[Mihran],
Detecting shopper groups in video sequences,
AVSBS07(417-422).
IEEE DOI
0709
BibRef
Zhang, Z.[Zhong],
Scanlon, A.[Andrew],
Yin, W.H.[Wei-Hong],
Yu, L.[Li],
Venetianer, P.L.[Peter L.],
Video Surveillance using a Multi-Camera Tracking and Fusion System,
M2SFA208(xx-yy).
0810
BibRef
Venetianer, P.L.,
Zhang, Z.,
Scanlon, A.,
Hu, Y.,
Lipton, A.J.,
Video verification of point of sale transactions,
AVSBS07(411-416).
IEEE DOI
0709
BibRef
Zimmerman, T.G.[Thomas G.],
Tracking Shopping Carts Using Mobile Cameras Viewing Ceiling-Mounted
Retro-Reflective Bar Codes,
CVS06(36).
IEEE DOI
0602
BibRef
Mustafa, A.,
Sethi, I.,
Detecting retail events using moving edges,
AVSBS05(626-631).
IEEE DOI
0602
BibRef
Haritaoglu, I.,
Flickner, M.D.,
Detection and Tracking of Shopping Groups in Stores,
CVPR01(I:431-438).
IEEE DOI
0110
BibRef
Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Surveillance Systems, Applied to Fire and Flame Detection .