@inproceedings{ed1d37857f52412ba61041c391531c85,
title = "Shopper behaviour analysis based on 3D situation awareness information",
abstract = "The customer behaviour understanding is of major importance to brick and mortar retail struggling to keep their market share and competing with online retail. In this paper, we propose a customer behaviour tracking solution based on 3D data. We can cover large areas using numerous inexpensive networked 3D sensors for monitoring and tracking people and we have adopted an adaptive background model in order to be able to react to changes in the store environment. Experiments with people tracking and analysis of the trajectories in a department store show that use of inexpensive 3D sensors and lightweight computation allows classifying shopping behaviour into three classes (passers-by, decisive customers, exploratory customers) with 80 % accuracy.",
keywords = "behaviour analysis, shopper behaviour, depth sensor based people tracking, depth sensor based situtation awareness",
author = "Satu-Marja M{\"a}kel{\"a} and Sari J{\"a}rvinen and Tommi Ker{\"a}nen and Mikko Lindholm and Elena Vildjiounaite",
year = "2014",
doi = "10.1007/978-3-319-12811-5_10",
language = "English",
isbn = "978-3-319-12810-8",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "134--145",
booktitle = "Video Analytics for Audience Measurement",
address = "Germany",
note = "Video Analytics for Audience Measurement: First International Workshop, VAAM 2014, 24 August 2014, Stockholm, Sweden ; Conference date: 24-08-2014",
}