ESR photo Research project "Context recognition for the application of visual privacy" About the project Most works conceal people’s visual privacy by using blurring or pixelating effects to modify an image. In a privacy-by-context approach, a level-based visualisation scheme to protect privacy is proposed. Each level establishes the way in which the video images are modified and displayed and, therefore, the provided protection degree. In this scheme, the appropriate level is dynamically selected according to the context, therefore modifying a non-protected image before it is displayed. The context has to provide enough information in order to empower people to adapt privacy to their preferences, in such a way that they can decide by whom, how and when they can be watched. The context is modelled by different variables: (i) the observer; (ii) the identity of the person (to retrieve the privacy profile); (iii) the closeness between the person and observer (e.g., relative, doctor or acquaintance); (iv) appearance (dressed?); (v) location (e.g., kitchen); and (vi) ongoing activity or detected event (e.g., cooking, watching TV, fall). Therefore, an accurate recognition of the context is paramount to provide the appropriate privacy level. This project will investigate techniques to recognise accurately these variables and it will validate them under different use case scenarios. Start date: April 2021 Expected end date: April 2024 Progress of the project The first variable to be addressed in this project has been appearance recognition and nudity detection in private spaces. During the first months, a literature review on nudity recognition has been carried out. The next step was to develop machine learning methods for nudity recognition using deep learning. However, the main problem with these methods is that the require large amounts of data and the available datasets were either small or low quality. Therefore, by using datasets for homogenous tasks such as garment recognition, a new skin dataset has been created as an extension of the FashionPedia garment and clothing dataset. In collaboration with ESR1, who has studied nudity from the social science discipline, a study over focus group has been done and then a methodology for nudity level recognition has been developed based on that study. Recently, using this knowledge, ESR14 has developed a deep learning method for skin segmentation integrating state-of-the-art semantic segmentation and attention models. Scientific publications Weakly supervised human skin segmentation using guidance attention mechanisms Kooshan Hashemifard, Pau Climent-Perez, Francisco Florez-Revuelta Weakly supervised human skin segmentation using guidance attention mechanisms Multimedia Tools and Applications, 2023 ODIN: An OmniDirectional INdoor dataset capturing Activities of Daily Living from multiple synchronized modalities Siddharth Ravi, Pau Climent-Perez, Théo Morales, Carlo Huesca-Spairani, Kooshan Hashemifard, Francisco Florez-Revuelta ODIN: An OmniDirectional INdoor dataset capturing Activities of Daily Living from multiple synchronized modalities 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Vancouver, BC, Canada, 2023, pp. 6488-6497 A Fallen Person Detector with a Privacy-Preserving Edge-AI Camera Kooshan Hashemifard, Francisco Florez-Revuelta, Gerard Lacey A Fallen Person Detector with a Privacy-Preserving Edge-AI Camera In Proceedings of the 9th International Conference on Information and Communication Technologies for Ageing Well and e-Health ICT4AWE - Volume 1, 262-269, Prague, Czech Republic, 2023 Underneath Your Clothes: A Social and Technological Perspective on Nudity in The Context of AAL Technology Caterina Maidhof, Kooshan Hashemifard, Julia Offermann, Martina Ziefle, Francisco Florez-Revuelta Underneath Your Clothes: A Social and Technological Perspective on Nudity in The Context of AAL Technology In Proceedings of the 15th International Conference on PErvasive Technologies Related to Assistive Environments, pp. 439-445, 2022. From Garment to Skin: The visuAAL Skin Segmentation Dataset Kooshan Hashemifard, Francisco Florez-Revuelta From Garment to Skin: The visuAAL Skin Segmentation Dataset In International Conference on Image Analysis and Processing. Springer, Cham, pp. 59-70, 2022. About the ESR Kooshan obtained his bachelor degree in Electrical Engineering (2015) from KNTU and a master’s degree focused on Signal Processing (2018) from Iran Broadcasting University. During his studies, he mainly explored the field of machine learning and after graduation, he worked as a Computer Vision engineer in different startups in Iran and developed large-scale machine learning services. Contact information Kooshan Hashemifard University of Alicante Department of Computing Technology Ctra. San Vicente del Raspeig, S/N 03690 San Vicente del Raspeig, Spain Email address: k.hashemifard@ua.es
Weakly supervised human skin segmentation using guidance attention mechanisms Kooshan Hashemifard, Pau Climent-Perez, Francisco Florez-Revuelta Weakly supervised human skin segmentation using guidance attention mechanisms Multimedia Tools and Applications, 2023
ODIN: An OmniDirectional INdoor dataset capturing Activities of Daily Living from multiple synchronized modalities Siddharth Ravi, Pau Climent-Perez, Théo Morales, Carlo Huesca-Spairani, Kooshan Hashemifard, Francisco Florez-Revuelta ODIN: An OmniDirectional INdoor dataset capturing Activities of Daily Living from multiple synchronized modalities 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Vancouver, BC, Canada, 2023, pp. 6488-6497
A Fallen Person Detector with a Privacy-Preserving Edge-AI Camera Kooshan Hashemifard, Francisco Florez-Revuelta, Gerard Lacey A Fallen Person Detector with a Privacy-Preserving Edge-AI Camera In Proceedings of the 9th International Conference on Information and Communication Technologies for Ageing Well and e-Health ICT4AWE - Volume 1, 262-269, Prague, Czech Republic, 2023
Underneath Your Clothes: A Social and Technological Perspective on Nudity in The Context of AAL Technology Caterina Maidhof, Kooshan Hashemifard, Julia Offermann, Martina Ziefle, Francisco Florez-Revuelta Underneath Your Clothes: A Social and Technological Perspective on Nudity in The Context of AAL Technology In Proceedings of the 15th International Conference on PErvasive Technologies Related to Assistive Environments, pp. 439-445, 2022.
From Garment to Skin: The visuAAL Skin Segmentation Dataset Kooshan Hashemifard, Francisco Florez-Revuelta From Garment to Skin: The visuAAL Skin Segmentation Dataset In International Conference on Image Analysis and Processing. Springer, Cham, pp. 59-70, 2022.