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While the appeal and utility of wearable camera devices for human-behavior understanding is indisputable, privacy concerns have limited the broader adoption of this method. To mitigate this problem, we propose a deep learning-based approach that recognizes everyday activities in egocentric photos that have been intentionally degraded in quality to preserve the privacy of bystanders. An evaluation on 2 annotated datasets collected in the field with a combined total of 84,078 egocentric photos showed activity recognition performance with accuracy between 79% and 88% across 17 and 21 activity classes when the images were subjected to blurring (mean filter k=20). To confirm that image degradation does indeed raise the perception of bystander privacy, we conducted a crowd sourced validation study with 640 participants; it showed a statistically significant positive relationship between the amount of image degradation and participants' willingness to be captured by wearable cameras. This work contributes to the field of privacy-sensitive activity recognition with egocentric photos by highlighting the trade-off between perceived bystander privacy protection and activity recognition performance.<\/jats:p>","DOI":"10.1145\/3161190","type":"journal-article","created":{"date-parts":[[2018,1,9]],"date-time":"2018-01-09T13:26:11Z","timestamp":1515504371000},"page":"1-18","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":56,"title":["Mitigating Bystander Privacy Concerns in Egocentric Activity Recognition with Deep Learning and Intentional Image Degradation"],"prefix":"10.1145","volume":"1","author":[{"given":"Mariella","family":"Dimiccoli","sequence":"first","affiliation":[{"name":"University of Barcelona and Computer Vision Center, Barcelona, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Juan","family":"Mar\u00edn","sequence":"additional","affiliation":[{"name":"University of Barcelona, Barcelona, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Edison","family":"Thomaz","sequence":"additional","affiliation":[{"name":"University of Texas at Austin, Department of Electrical and Computer Engineering, Austin, TX, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2018,1,8]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Prototypes and paratypes: Designing mobile and ubiquitous computing applications","author":"Abowd Gregory D","year":"2005","unstructured":"Gregory D Abowd , Gillian R Hayes , Giovanni Iachello , Julie A Kientz , Shwetak N Patel , Molly M Stevens , and Khai N Truong . 2005. 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