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Handheld object detection and its related event analysis using ratio histogram and mixture of HMMs

机译:使用比率直方图和HMM混合进行手持物体检测及其相关事件分析

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摘要

This paper proposes a novel system to analyze human-object interaction events happening between hands and faces in real time. Two challenging problems in this event analysis must be addressed, i.e., there is no prior knowledge (like shape, color, size, and texture) about the handheld objects, and there are large spatial-temporal variations in event representation. For the first challenge, a novel ratio histogram is proposed to find important color bins to locate handheld objects and their trajectories via a code book technique. This scheme is different from other boosted methods which require very time-consuming estimations to search reliable body configurations. For the second challenge, a mixture of HMMs is proposed to describe an event not only from its dynamic context but also its multiplicity context. It can be performed in real time because an exhaustive search process is avoided to find possible interaction pairs between objects and body parts.
机译:本文提出了一种新颖的系统来实时分析手和脸之间发生的人-物体交互事件。在此事件分析中必须解决两个具有挑战性的问题,即,没有关于手持对象的先验知识(例如形状,颜色,大小和纹理),并且事件表示中存在较大的时空变化。对于第一个挑战,提出了一种新颖的比率直方图,以通过代码本技术找到重要的色块,以定位手持对象及其轨迹。该方案不同于其他增强方法,后者需要非常耗时的估计来搜索可靠的身体构型。对于第二个挑战,提出了混合HMM来不仅从事件的动态上下文而且从其多重性上下文描述事件。它可以实时执行,因为避免了详尽的搜索过程来查找对象与身体部位之间可能的交互对。

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