Fusing WiFi and video sensing for accurate group detection in indoor spaces
Understanding one's group context in indoor spaces is useful for many reasons - e.g., at a shopping mall, knowing a customer's group context can help in offering context-specific incentives, or estimating taxi demand for customers exiting the mall. Group detection and monitoring using WiFi...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | text |
| Language: | English |
| Published: |
Institutional Knowledge at Singapore Management University
2016
|
| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/sis_research/3636 https://ink.library.smu.edu.sg/context/sis_research/article/4638/viewcontent/wpa16_group.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Singapore Management University |
| Language: | English |
| Summary: | Understanding one's group context in indoor spaces is useful for many reasons - e.g., at a shopping mall, knowing a customer's group context can help in offering context-specific incentives, or estimating taxi demand for customers exiting the mall. Group detection and monitoring using WiFi-based indoor location traces fails when users are invisible (either because they don't carry smartphones, or because their WiFi is turned OFF) or when location tracking is inaccurate. In this paper, we propose a multi-modal group detection system that fuses two independent modes: video and WiFi, for detecting groups with low latency and high accuracy. We present preliminary results from a micro-study with 20 group episodes and report an overall precision of 0.81 and recall of 0.9, an improvement of over ≈20% over WiFi-based group detection. |
|---|