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.
翻译:以地球为中心的视觉环境检测可以支持智能增强应用。 我们创建了一个可磨损系统,名为PAL,用于磨损、个性化和隐私保护自我中心视觉环境检测。 PAL拥有一个可磨损设备,带有相机、心率传感器、设备深层学习和音频输入/输出。 PAL还有个性化环境标签的移动/网络应用程序。 我们使用了用于普通物体和面部检测、低镜头自定义脸部和背景识别(如刷牙等活动)和定制环境群集(如室内地点)的深深层学习模型。 这些模型在边缘环境中有80%的精度(~1000图像),我们测试了智能增强应用程序,如行为变化。 我们让 PAL成为了进一步支持智能增强的开源,使用个性化和隐私保护自我中心视觉环境。