OBJECT DETECTION AND TRACKING IN THERMAL VIDEO USING DIRECTED ACYCLIC GRAPH (DAG)

Supriya Mangale, R. Tambe, M. Khambete
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引用次数: 8

Abstract

This paper suggests an incipient approach to perform target detection as well as tracking for single and multiple moving objects in thermal video sequences. Thermal imaging is complimentary to visible imaging as it has capability to detect object in low light or dark conditions by detecting the infrared radiation of an object and creating an image which contains temperature information. The extracted regions are then used for performing the segmentation of targets in thermal videos. In projected method first, Directed Acyclic Graph (DAG) is used for segmentation in thermal videos. Second, to enlarge the set of target proposals, DAG is initialized with an incremented object proposal set in which, from adjacent frames motion based predictions are used. Last, in this paper for selection of the specific object motion scoring function is used, which is having high optical flow gradient between the edges of the object and background is presented. After segmentation of object, centroid based object tracking is performed to track the objects in thermal videos. The proposed method is evaluated on different thermal videos and found to be robust compared with standard background subtraction method.
基于有向无环图的热视频目标检测与跟踪
本文提出了一种对热视频序列中单个和多个运动目标进行目标检测和跟踪的初步方法。热成像是对可见成像的补充,因为它能够通过检测物体的红外辐射并创建包含温度信息的图像来检测弱光或黑暗条件下的物体。然后使用提取的区域对热视频中的目标进行分割。在投影法中,首先使用有向无环图(DAG)对热视频进行分割。其次,为了扩大目标建议集,DAG使用增量目标建议集初始化,其中使用基于相邻帧的运动预测。最后,本文针对具体目标运动的选择,提出了目标边缘与背景之间具有高光流梯度的运动评分函数。在对目标进行分割后,采用基于质心的目标跟踪方法对热视频中的目标进行跟踪。在不同的热视频上对该方法进行了测试,结果表明该方法与标准背景减法相比具有较好的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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