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Sketches characterization and compression for nomadic computing

机译:草图表征和压缩,用于游牧计算

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Nomadic computing often refers to people using computer support working anywhere, anytime and not necessarily attached to a specific location or time of the day. Mobile computing and wireless ad-hoc networks are important elements in this kind of scenarios. Nowadays it is common to see architects, engineers, geologists and/or designers working on the field and sharing ideas on a collaborative media using sketches and freehand writing. On this scenario, data overflow among the peer applications often happens, since the sketches have to be distributed among all participants in real time. This paper presents a work on characterization and compression algorithms for sketches, with and without loss of information, to be used on mobile devices, in order to reduce the data traffic. We focused our study on three parameters of the algorithms: time required characterizing and compressing the sketch, size of the resulting information and human perceived of lost information. Our results present algorithms with a compression ratio lower than 1% the size of the original image without information loosing under human perception.
机译:游牧计算通常是指使用计算机支持的人们可以在任何地方,任何时间工作,而不必一定附加到一天中的特定位置或时间。在这种情况下,移动计算和无线自组织网络是重要的元素。如今,经常看到建筑师,工程师,地质学家和/或设计师在现场工作,并使用素描和徒手书写的方式在协作媒体上共享想法。在这种情况下,由于必须在所有参与者之间实时分发草图,因此经常会在对等应用程序之间发生数据溢出。本文介绍了在有信息丢失和无信息丢失的情况下草图的特征描述和压缩算法,该算法将在移动设备上使用,以减少数据流量。我们将研究重点放在算法的三个参数上:表征和压缩草图所需的时间,所得信息的大小以及人们对丢失信息的感知。我们的结果提出了一种算法,其压缩率低于原始图像大小的1%,而在人类感知下不会丢失信息。

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