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Detection and Tracking of Targets in Forward-Looking InfraRed (FLIR) Imagery

机译:前视红外(FLIR)图像中目标的检测和跟踪

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摘要

Detection and tracking of targets in forward looking infrared (FLIR) imagery are challenging tasks. IR sensors often provide low signal-to-noise ratio and heavy background cluttering images. Non-stationary cameras can introduce further challenges, because detection and tracking might make it necessary to properly deal with sensor ego-motion through suitable estimation and compensation techniques. Moreover, further issues are posed by imagery with multiple and possibly moving target and non-target objects, which can blend into the background, change their signature, size, shape, and even overlap during their motion. Finally, specific applications could introduce cumbersome real-time constraints, thus requiring tracking techniques with a reduced computational footprint.The objective of this Special Issue is to invite high state-of-the-art research contributions, tutorials, and position papers that address the broad challenges faced in analysis and processing of FLIR imagery. Original papers describing completed and unpublished work that are not currently under review by any other journal/magazine/conference/special issue are solicited.
机译:前视红外(FLIR)图像中目标的检测和跟踪是一项艰巨的任务。红外传感器通常提供低信噪比和沉重的背景杂乱图像。非平稳摄像机可能会带来进一步的挑战,因为检测和跟踪可能需要通过适当的估计和补偿技术正确处理传感器的自我运动。此外,具有多个并可能移动的目标对象和非目标对象的图像提出了进一步的问题,这些对象可以融合到背景中,改变其特征,大小,形状,甚至在运动过程中重叠。最后,特定的应用程序可能会引入繁琐的实时约束,因此需要具有减少计算占用空间的跟踪技术。本期特刊的目的是邀请高水平的研究论文,教程和立场文件来解决这些问题。 FLIR图像分析和处理中面临的广泛挑战。征集描述已完成和未发表作品的原始论文,目前尚未由任何其他期刊/杂志/会议/特殊刊物进行审查。

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