TY  - JOUR
AU  - Khalid El Asnaoui
AU  - Petia Radeva
PY  - 2020//
TI  - Automatically Assess Day Similarity Using Visual Lifelogs
T2  - IJIS
JO  - International Journal of Intelligent Systems
SP  - 298–310
VL  - 29
N2  - Today, we witness the appearance of many lifelogging cameras that are able to capture the life of a person wearing the camera and which produce a large number of images everyday. Automatically characterizing the experience and extracting patterns of behavior of individuals from this huge collection of unlabeled and unstructured egocentric data present major challenges and require novel and efficient algorithmic solutions. The main goal of this work is to propose a new method to automatically assess day similarity from the lifelogging images of a person. We propose a technique to measure the similarity between images based on the Swain’s distance and generalize it to detect the similarity between daily visual data. To this purpose, we apply the dynamic time warping (DTW) combined with the Swain’s distance for final day similarity estimation. For validation, we apply our technique on the Egocentric Dataset of University of Barcelona (EDUB) of 4912 daily images acquired by four persons with preliminary encouraging results.
UR  - https://doi.org/10.1515/jisys-2017-0364
N1  - MILAB; no proj
ID  - Khalid El Asnaoui2020
ER  -