使用SlowFast和CNN检测CCTV日托视频中被识别儿童的活动和情绪

Narayana Darapaneni, Dhirendra Singh, Sharat P Chandra, A. Paduri, Neeraj Kilhore, Shivangi Chopra, Akash Srivastav, Rashmi Tomer, Sudhershan Sureshrao Deshmukh
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引用次数: 4

摘要

对于工作的父母来说,现实生活中面临的一个挑战是跟踪他们的孩子在幼儿园和幼儿园的活动。尽管家长可以使用闭路电视监控,但每天监控8-10小时的视频是不可能的,因此,CCTV视频中包含了数百万信息,却被父母和托儿所所忽视。该项目的目的是通过处理闭路电视视频来识别孩子,检测他们各自的表情以及一天中计划/计划外的活动。我们认为孩子们的愤怒、厌恶、害怕、快乐、悲伤、惊讶、中性的表情是每天都要监控的。在日托所进行的各种活动,如玩耍,画画,押韵,跳舞,以及不太常见的活动,如拍打,摔倒,推,也会对孩子们进行监控。可以进一步扩展,以视频/时间轴的形式制作8-10分钟的儿童全天活动概览/总结,并告知各自的家长。这可以为父母即兴创造日托的整体体验。
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Activity & Emotion Detection of Recognized kids in CCTV Video for Day Care Using SlowFast & CNN
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.
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