Abstract
Video representation is a key challenge in many computer vision applications such as video classification, video captioning, and video surveillance. In this paper, we propose a novel approach for video representation that captures meaningful information including motion and appearance from a sequence of video frames and compacts it into a single image. To this end, we compute the optical flow and use it in a least squares optimization to find a new image, the so-called Flow Profile Image (FPI). This image encodes motions as well as foreground appearance information while background information is removed. The quality of this image is validated in activity recognition experiments and the results are compared with other video representation techniques such as dynamic images [1] and eigen images [2]. The experimental results as well as visual quality confirm that FPIs can be successfully used in video processing applications.
Abstract (translated)
视频表示是许多计算机视觉应用中的一个关键挑战，如视频分类、视频字幕和视频监控。在本文中，我们提出了一种新的视频表示方法，它从一系列视频帧中捕获有意义的信息，包括运动和外观，并将其压缩为单个图像。为此，我们对光流进行了计算，并将其应用于最小二乘法优化，得到一幅新的图像，即所谓的流剖面图像（FPI）。此图像在删除背景信息时对运动和前景外观信息进行编码。在活动识别实验中验证了该图像的质量，并与动态图像[1]和特征图像[2]等其他视频表示技术进行了比较。实验结果和视觉质量都证实了该系统可以成功地应用于视频处理领域。
URL
https://arxiv.org/abs/1905.04668
