Improving Food Detection For Images From a Wearable Egocentric Camera

no code implementations • 19 Jan 2023 • Yue Han, Sri Kalyan Yarlagadda, Tonmoy Ghosh, Fengqing Zhu, Edward Sazonov, Edward J. Delp

In this paper, we propose an approach to pre-process images collected by the AIM imaging sensor by rejecting extremely blurry images to improve the performance of food detection.

Clustering Egocentric Images in Passive Dietary Monitoring with Self-Supervised Learning

no code implementations • 25 Aug 2022 • Jiachuan Peng, Peilun Shi, Jianing Qiu, Xinwei Ju, Frank P. -W. Lo, Xiao Gu, Wenyan Jia, Tom Baranowski, Matilda Steiner-Asiedu, Alex K. Anderson, Megan A McCrory, Edward Sazonov, Mingui Sun, Gary Frost, Benny Lo

By clustering images into separate events, annotators and dietitians can examine and analyze the data more efficiently and facilitate the subsequent dietary assessment processes.

Clustering Self-Supervised Learning

Egocentric Image Captioning for Privacy-Preserved Passive Dietary Intake Monitoring

no code implementations • 1 Jul 2021 • Jianing Qiu, Frank P. -W. Lo, Xiao Gu, Modou L. Jobarteh, Wenyan Jia, Tom Baranowski, Matilda Steiner-Asiedu, Alex K. Anderson, Megan A McCrory, Edward Sazonov, Mingui Sun, Gary Frost, Benny Lo

In this paper, we propose a privacy-preserved secure solution (i. e., egocentric image captioning) for dietary assessment with passive monitoring, which unifies food recognition, volume estimation, and scene understanding.

Food Recognition Image Captioning +1