mlsanityData to 14 Oct 2026

PAL: Intelligence Augmentation using Egocentric Visual Context Detection

arXiv 2105.10735 ↗First posted 22 May 2021cs.CV cs.AI cs.HCcited by 1

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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

  1. 2014Microsoft COCO: Common Objects in Contextcited by 17,608
  2. 2017MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applicationscited by 3,845
  3. 2015SSD: Single Shot MultiBox Detectorcited by 3,130
  4. 2015FaceNet: A Unified Embedding for Face Recognition and Clusteringcited by 2,849
  5. 2015Predicting Daily Activities From Egocentric Images Using Deep Learningcited by 3
  6. 2019PAL: A Wearable Platform for Real-time, Personalized and Context-Aware Health and Cognition Supportcited by 1

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