Finding periodicity in space and time

被引：64

作者：

Liu, F ^{[1
]}

Picard, RW ^{[1
]}

机构：

[1] MIT, Media Lab, Cambridge, MA 02139 USA

来源：

SIXTH INTERNATIONAL CONFERENCE ON COMPUTER VISION | 1998年

关键词：

D O I：

10.1109/ICCV.1998.710746

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

An algorithm for simultaneous detection, segmentation, and characterization of spatiotemporal periodicity is presented. The use of periodicity templates is proposed to localize and characterize temporal activities. The templates not only indicate the presence and location of a periodic event, but also give an accurate quantitative periodicity measure. Hence, they can be used as a new means of periodicity representation. The proposed algorithm can also be considered as a "periodicity filter," a low-level model of periodicity perception. The algorithm is computationally simple, and shown to be more robust than optical flow based techniques in the presence of noise. A variety of real world examples are used to demonstrate the performance of the algorithm.

引用

页码：376 / 383

页数：8