Smart mirror application for social event based outfit recommendation and skin health analysis

dc.contributor.authorRathnasekara, N
dc.contributor.authorDamith, N
dc.contributor.authorHerath, D
dc.contributor.authorSeneviratne, O
dc.contributor.authorWijenayake, U
dc.contributor.editorAthuraliya, CD
dc.date.accessioned2025-11-24T04:08:39Z
dc.date.issued2025
dc.description.abstractThe rapid evolution of Artificial Intelligence(AI) has paved the way for innovative applications in everyday objects. Among these, a smart mirror is a representation of a traditional mirror with integrated technologies to provide realtime personalized recommendations and health insights. Busy schedules make it challenging for individuals to manage their to-do lists, health, and even dress code choices. According to the past work done, both Khandaker et al. [1] and Simone et al. [2] developed smart mirrors with various features, such as face verification, weather updates, calendar events, news, traffic, and emotion recognition. Considering social event-based fashion recommendation, Federico et al [3] proposed an event classifier combined with a recommender by implementing a fashion object detector for social events. Nikita et al [4] proposed outfit recommendation by detecting user outfits, identifying the social event, and suggesting similar outfits for the detected event. However the system lacks the ability of considering outfits suitable for multiple social events. In the context of acne detection, Quan et al. [5] proposed an automatic system that employs Faster Region-based Convolutional Neural Network (R-CNN) for acne lesion detection and LightGBM for severity grading. Similarly, Hang et al. [6] introduced an ensemble neural network-based approach featuring a classification module for severity estimation and an acne localization module. However, prior research has focused on general acne detection, there is limited work addressing localizing acne within the ”Danger Triangle of the Face” which is a crucial clinical aspect. This research proposes a comprehensive Internet of Things(IoT) smart mirror framework to address past limitations. Mainly, it has features for face verification, acne detection with ”Triangle of Death” localization, and social event-based fashion recommendation. By leveraging these components, the proposed smart mirror represents a significant advancement towards smart computing, seamlessly integrated with digital intelligence.
dc.identifier.conferenceApplied Data Science & Artificial Intelligence (ADScAI) Symposium 2025
dc.identifier.departmentDepartment of Computer Science & Engineering
dc.identifier.doihttps://doi.org/10.31705/ADScAI.2025.20
dc.identifier.emailprabuddhi.rath2@gmail.com
dc.identifier.emailnisaladamith99@gmail.com
dc.identifier.emaildasuninimesha99@gmail.com
dc.identifier.emailoviniseneviratne@sjp.ac.lk
dc.identifier.emailudayaw@sjp.ac.lk
dc.identifier.facultyEngineering
dc.identifier.placeMoratuwa, Sri Lanka
dc.identifier.proceedingProceedings of Applied Data Science & Artificial Intelligence Symposium 2025
dc.identifier.urihttps://dl.lib.uom.lk/handle/123/24448
dc.language.isoen
dc.publisherDepartment of Computer Science and Engineering
dc.subjectacne detection
dc.subjectface recognition
dc.subjectfashion recommendation
dc.subjectIoT
dc.subjectsmart mirror
dc.titleSmart mirror application for social event based outfit recommendation and skin health analysis
dc.typeConference-Extended-Abstract

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