Visual analysis of child-adult interactive behaviors in video sequences

Ye Liu, Xinye Zhang, J. Cui, Chen Wu, H. Aghajan, H. Zha
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引用次数: 72

Abstract

Kids activity means a lot to their parents, and in the analysis of the activities, video retrieval has played an important role. In this paper, we propose an effective approach for the retrieval of the kid's activities from home videos. The video sequences are taken from our test-bed environment that is designed in the form of a smart home, and feature various types of child-adult interactions. We present a novel retrieval method with two steps, first using spatio-temporal matching to obtain a coarse result, And then we propose a method to learn dominant child-adult interactive behaviors based on a sequence of home videos. Based on these dominant behaviors, we get rid of some false retrieval and obtain fine result. We implement and test our methodology on a newly-introduced dataset containing several types of kid's activities, and the retrieval result shows its potential application in the video analysis demain, it can find out most of the video clips relevant to the query one.
视频序列中儿童-成人互动行为的视觉分析
孩子的活动对家长来说意义重大,在对孩子活动的分析中,视频检索起到了重要的作用。在本文中,我们提出了一种从家庭录像中检索儿童活动的有效方法。视频序列取自我们的测试平台环境,该环境以智能家居的形式设计,并具有各种类型的儿童-成人互动。本文提出了一种新的检索方法,首先利用时空匹配得到一个粗略的结果,然后我们提出了一种基于家庭视频序列的儿童-成人主导互动行为的学习方法。基于这些主导行为,我们消除了一些错误的检索,得到了较好的结果。我们在一个新引入的包含多种儿童活动类型的数据集上实现并测试了我们的方法,检索结果显示了它在视频分析领域的潜在应用,它可以找到与查询内容相关的大部分视频片段。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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