mlsanityData to 14 Oct 2026

RetailOpt: Opt-In, Easy-to-Deploy Trajectory Estimation from Smartphone Motion Data and Retail Facility Information

arXiv 2404.12548 ↗First posted 19 Apr 2024cs.AI cs.ROcited by 3

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Abstract (arXiv)

We present RetailOpt, a novel opt-in, easy-to-deploy system for tracking customer movements offline in indoor retail environments. The system uses readily accessible information from customer smartphones and retail apps, including motion data, store maps, and purchase records. This eliminates the need for additional hardware installations/maintenance and ensures customers full data control. Specifically, RetailOpt first uses inertial navigation to recover relative trajectories from smartphone motion data. The store map and purchase records are cross-referenced to identify a list of visited shelves, providing anchors to localize the relative trajectories in a store through continuous and discrete optimization. We demonstrate the effectiveness of our system in five diverse environments. The system, if successful, would produce accurate customer movement data, essential for a broad range of retail applications including customer behavior analysis and in-store navigation.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 12 of its 63 references that are in the map. First posted on arXiv 19 Apr 2024.

Builds on

12 of 63 references.

References · 12

  1. 2017Attention Is All You Needcited by 60,361
  2. 2016Image-based localization using LSTMs for structured feature correlationcited by 136
  3. 2019Learning Regularity in Skeleton Trajectories for Anomaly Detection in Videoscited by 104
  4. 2017A Survey of Indoor Localization Systems and Technologiescited by 78
  5. 2019RoNIN: Robust Neural Inertial Navigation in the Wild: Benchmark, Evaluations, and New Methodscited by 73
  6. 2024RTAB-Map as an Open-Source Lidar and Visual SLAM Library for Large-Scale and Long-Term Online Operationcited by 62
  7. 2019Multi-timescale Trajectory Prediction for Abnormal Human Activity Detectioncited by 59
  8. 2023NeRF2: Neural Radio-Frequency Radiance Fieldscited by 57
  9. 2020TLIO: Tight Learned Inertial Odometrycited by 55
  10. 2017RIDI: Robust IMU Double Integrationcited by 41
  11. 2021IDOL: Inertial Deep Orientation-Estimation and Localizationcited by 26
  12. 2021Fusion-DHL: WiFi, IMU, and Floorplan Fusion for Dense History of Locations in Indoor Environmentscited by 8

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 2; 2026: 1.

3 papers.