PAL: Intelligence Augmentation using Egocentric Visual Context Detection
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Abstract (arXiv)
Egocentric visual context detection can support intelligence augmentation applications. We created a wearable system, called PAL, for wearable, personalized, and privacy-preserving egocentric visual context detection. PAL has a wearable device with a camera, heart-rate sensor, on-device deep learning, and audio input/output. PAL also has a mobile/web application for personalized context labeling. We used on-device deep learning models for generic object and face detection, low-shot custom face and context recognition (e.g., activities like brushing teeth), and custom context clustering (e.g., indoor locations). The models had over 80% accuracy in in-the-wild contexts (~1000 images) and we tested PAL for intelligence augmentation applications like behavior change. We have made PAL is open-source to further support intelligence augmentation using personalized and privacy-preserving egocentric visual contexts.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 6 of its 32 references that are in the map. First posted on arXiv 22 May 2021.
Builds on
6 of 32 references.
References · 6
- 2014Microsoft COCO: Common Objects in Contextcited by 17,608
- 2017MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applicationscited by 3,845
- 2015SSD: Single Shot MultiBox Detectorcited by 3,130
- 2015FaceNet: A Unified Embedding for Face Recognition and Clusteringcited by 2,849
- 2015Predicting Daily Activities From Egocentric Images Using Deep Learningcited by 3
- 2019PAL: A Wearable Platform for Real-time, Personalized and Context-Aware Health and Cognition Supportcited by 1
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Citing papers per year: 2021: 1.
1 paper.
- 2021Personalizing Pre-trained Modelscited by 5
- 2021Personalizing Pre-trained Models2 Jun 2021