Activity & Emotion Detection of Recognized kids in CCTV Video for Day Care Using SlowFast & CNN

Abstract

For working parents a real-life challenge faced is to keep track of their child activities in playschool and creche. Despite having CCTV surveillance available to parents, monitoring 8–10 hours videos on a day-to-day basis is not possible, hence CCTV videos, which carry millions of information, get unnoticed by parents and day-cares. The aim of project was to process CCTV videos to identify the child, detect their respective expressions as well as planned/unplanned activities throughout the day. We have considered angry, disgust, scared, happy, sad, surprised, neutral expressions of kids to be monitored on daily basis. The various activities performed at daycare like playing, drawing, rhyming, dancing along with not so usual activities like slapping, falling, pushing would also be monitored on kids. It can be further extended to create a 8–10 minutes glimpse/summary in form of video/timeline of children's entire day activities and inform their respective parents. This can improvise the overall experience of the daycare for parents.