@InProceedings{MaedehAghaei2014,
author="Maedeh Aghaei
and Petia Radeva",
title="Bag-of-Tracklets for Person Tracking in Life-Logging Data",
booktitle="17th International Conference of the Catalan Association for Artificial Intelligence",
year="2014",
volume="269",
pages="35--44",
abstract="By increasing popularity of wearable cameras, life-logging data analysis is becoming more and more important and useful to derive significant events out of this substantial collection of images. In this study, we introduce a new tracking method applied to visual life-logging, called bag-of-tracklets, which is based on detecting, localizing and tracking of people. Given the low spatial and temporal resolution of the image data, our model generates and groups tracklets in a unsupervised framework and extracts image sequences of person appearance according to a similarity score of the bag-of-tracklets. The model output is a meaningful sequence of events expressing human appearance and tracking them in life-logging data. The achieved results prove the robustness of our model in terms of efficiency and accuracy despite the low spatial and temporal resolution of the data.",
optnote="MILAB",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=2607), last updated on Tue, 15 Dec 2015 13:56:08 +0100",
isbn="978-1-61499-451-0",
doi="10.3233/978-1-61499-452-7-35"
}