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本文为捷克共和国布尔诺理工大学(作者:Ing. Igor Potúček)的博士论文,共101页。
本文研究了全方位人体活动检测与跟踪系统的建立和方法。关于全方位系统的研究越来越多,原因在于它具有成本低、可移植性好、安装方便等优点。它的主要优点是可以捕捉到一个很大一部分的空间角度,即360度。另一方面,存在着许多问题必须加以解决。全向系统的图像具有不同于标准透视图像的特性,因为它们具有较低的有效分辨率和不利的图像失真。如果要将得到的图像呈现给人或进一步处理,则必须进行变换和适当的校正。
本文提出了将图像变换成透视图或全景图以及几何校正的方法。移动折反射系统通常容易发生振动,导致变换后的全景图像失真。为此,提出了一种新的全向系统图像稳定方法。人脸和手部检测在视频监控、人机界面、人脸识别等应用中起着重要的作用,广角视角对这类任务非常重要,因此,全方位的检测系统非常适合于这类任务。对全向系统捕获的各种视频序列,比较了两种不同的跟踪方法,以说明全向系统与所提出方法的优缺点。提出了一种评价方案,对不同视频源进行了定性和定量的算法描述和比较。
This work investigates the setup and the set of methods ofomni-directional system for human activity detection and tracking. Research inthe area of the omni-directional systems is growing, the reason are many advantages such as low cost, portability and easy installation. The main advantage is capturing a large portion of a space angle, which is 360 degrees. On the other hand, a lotof problems exist and they must be solved. Images from omni-directionalsystems have different properties than standard perspective images as they have lower effective resolution and suffer adverse image distortion. If the resulting image is to be presented to a human or is furtherprocessed, transformation and suitable kind of corrections must be done.Techniques for image transformation into a perspective or panoramic view andgeometrical corrections are suggested in this paper. The mobile catadioptricsystem is usually prone to vibrations, which cause the distortion in the transformedpanoramic image. Therefore the novel approach for stabilization of the imagefrom omni-directional system was proposed. Human face and hands detection plays an important role in applications such as video surveillance, human computer interface, face recognition, etc. The wide view angle is important for this kind of tasks and therefore the omni-directionalsystem is suitable for these purposes. Two different tracking methods are compared on the various kinds of video sequences captured by omni-directional system in order to demonstrate the benefits and/or drawbacks of the omni-directional system and proposed methods.The evaluation scheme was developed for qualitative and quantitative algorithm description and comparison on different video sources.
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