PT Unknown
AU Maedeh Aghaei
   Petia Radeva
TI Bag-of-Tracklets for Person Tracking in Life-Logging Data
BT 17th International Conference of the Catalan Association for Artificial Intelligence
PY 2014
BP 35
EP 44
VL 269
DI 10.3233/978-1-61499-452-7-35
AB 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.
ER