Privacy behaviors of lifeloggers using wearable cameras

222 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

I-Pic: A Platform for Privacy-Compliant Image Capture (2016, background): “[33] seek to understand users’ concerns about continuous recording using wearable cameras, by studying a large user population of avid life-loggers.”
Privacy Concerns and Behaviors of People with Visual Impairments (2015, background): “This suggests that more work is needed on how to detect private content in images automatically, a problem that has recently been studied in the context of camera-based lifelogging [14,30].”
Enhancing Lifelogging Privacy by Detecting Screens (2016, methodology): “We investigate the extent to which emerging state-of-the-art computer vision techniques based on deep learning [23] can identify monitors in real lifelogs, using a dataset collected by 36 participants during a week-long, in situ study [16].”
Privacy-Preserving Visual Learning Using Doubly Permuted Homomorphic Encryption (2017, background): “Interestingly, we do not always share captured data publicly but just store it on a personal storage [32], and such private data contains various moments of everyday life that are not found in publicly shared data [5, 11, 31, 33].”
Deepdiary: Lifelogging image captioning and summarization (2018, background): “[39] identify privacy risks to the camera wearers themselves.”