基于LogGabor-PCA方法的视频多运动目标检测
Multiple Moving Object Recognitions in video based on Log Gabor-PCA Approach
摘要：
视频序列或图像中的目标识别是计算机视觉的一个分支。从视频序列中识别运动目标是一个很有吸引力的课题，在机场安全，入侵监视，视频监控，智能高速公路等领域的应用。运动目标识别是智能视频监控系统中最具挑战性的任务。在这方面，已经基于不同的方法提出了许多技术。尽管它的重要性，在复杂环境中的运动目标识别仍然远远没有完全解决低分辨率视频，雾视频，也暗淡的视频序列。总而言之，这些使得有必要开发非常强大的技术。本文介绍了多个运动目标识别的视频序列的基础上LoG的Gabor-PCA方法和角度的距离相似性措施的技术，用于识别对象作为一个人，车辆等进行了实验的数量为室内和室外的视频序列的标准数据集，也是我们自己收集的视频序列，包括部分夜视视频序列。实验结果表明，我们提出的方法取得了良好的识别率。所得结果令人满意且合格。
英文摘要：
Object recognition in the video sequence or images is one of the sub-field of computer vision. Moving object recognition from a video sequence is an appealing topic with applications in various areas such as airport safety, intrusion surveillance, video monitoring, intelligent highway, etc. Moving object recognition is the most challenging task in intelligent video surveillance system. In this regard, many techniques have been proposed based on different methods. Despite of its importance, moving object recognition in complex environments is still far from being completely solved for low resolution videos, foggy videos, and also dim video sequences. All in all, these make it necessary to develop exceedingly robust techniques. This paper introduces multiple moving object recognition in the video sequence based on LoG Gabor-PCA approach and Angle based distance Similarity measures techniques used to recognize the object as a human, vehicle etc. Number of experiments are conducted for indoor and outdoor video sequences of standard datasets and also our own collection of video sequences comprising of partial night vision video sequences. Experimental results show that our proposed approach achieves an excellent recognition rate. Results obtained are satisfactory and competent.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
