图像序列中基于片段的事件描述的发展

U. Thoennessen, D. Ernst, H. Gross
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引用次数: 1

摘要

本文描述了一种图像序列处理方法,该方法从图像序列中提取物体(或物体的一部分),生成特定运动属性的轨迹(位置/时间过程),并派生出运动层次。该基由由多阈值方法确定的对象表征段组成。该方法生成每个片段的特征描述。基于此描述,完成了帧与帧之间的段关联。只要片段的特征和特定于运动的属性不发生显著变化,生成的运动向量就会被连接起来。在随后的步骤中,执行轨道之间特定运动相互关系的分析。事件识别由事件模型进行处理和控制。与运动概念一致,事件的假设是由运动相关的轨迹变化初始化的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development of a segment-based description of events in image sequences
This paper describes an approach for image sequence processing, which extracts objects (or parts of objects) from the image sequence, generates motion-specifically attributed tracks (location/time course) and derives a hierarchy of motion. The base consists of object-characterizing segments which are determined by a multiple threshold method. This method yields feature descriptions for each segment. Based on this description, an association of the segments from frame to frame is done. The resulting motion vectors are concatenated as long as the features of the segments and the motion-specific attributes do not change significantly. In a subsequent step the analysis of motion-specific interrelations between the tracks is executed. The event recognition is processed and controlled by event models. In conformity with motion concepts the hypotheses of events are initialized by motion dependent changes of the tracks.<>
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