Research on algorithm for object tracking under circumstance of occlusion and semi- occlusion

运动目标跟踪技术是计算机视觉领域的核心课题之一，具有十分重要的意义和广泛的实用价值。它融合了图像处理、模式识别、人工智能、自动控制以及计算机应用等相关领域的先进技术和研究成果。运动目标跟踪的实质是一种从图像信号中实时自动识别目标，提取目标的位置信息，自动跟踪目标的技术。它的难点在于图像信号采集过程中的信息损失和复杂的应用环境。特别是跟踪过程中的遮挡问题越来越成为限制跟踪算法实用性的关键因素。如何解决运动目标跟踪过程中的遮挡问题是本文的研究重点。 针对运动目标的遮挡问题，本文提出了一种将基于灰度特征的多子区域相关跟踪算法与二维目标运动估计理论相结合的跟踪策略。在目标未被遮挡或仅被部分遮挡时，采用多子区域相关跟踪算法，利用目标剩余的特征对目标进行定位。当遮挡比较严重，目标剩余特征不足以准确定位目标位置或目标已被完全遮挡时，多子区域相关跟踪算法已经不能识别目标，这时根据目标运动的历史信息，运用二维目标运动估计理论预测出目标的位置。经过大量仿真试验，结果表明：该算法已经达到了良好的抗遮挡效果，在遮挡和半遮挡情况下，跟踪结果达到了较高的精度。 为了验证算法在实际工程中的效果，笔者模拟某红外观瞄指示装置，为算法搭建了一个基于虚拟现实技术的硬件验证平台，并在该平台上验证了部分算法

Online updating method for image compression dynamic regulation

本发明涉及一种图像压缩动态调整的在线更新方法，具体的说是在无线图像传输系统中通过动态计算修改量化系数QP实现图像压缩的动态调整。本发明根据H.264国际标准对YUV图像进行帧内预测和帧间预测，实现空间和时间相关性压缩；根据图像内容信息计算一个图像序列的关键参考帧的QP值；根据关键参考帧和其它帧的差异信息，计算其它帧的能量阈值，确定所述图像序列中所有帧的QP值；根据所述图像序列中所有帧的QP值，对所述图像序列进行量化处理，完成图像编码压缩。本发明可以根据图像内容信息进行动态修改量化系数QP的视频动态压缩，完成无线图像传输系统中图像压缩码率的在线更新

Online updating method for image compression dynamic regulation

本发明涉及一种图像压缩动态调整的在线更新方法，具体的说是在无线图像传输系统中通过动态计算修改量化系数QP实现图像压缩的动态调整。本发明根据H.264国际标准对YUV图像进行帧内预测和帧间预测，实现空间和时间相关性压缩；根据图像内容信息计算一个图像序列的关键参考帧的QP值；根据关键参考帧和其它帧的差异信息，计算其它帧的能量阈值，确定所述图像序列中所有帧的QP值；根据所述图像序列中所有帧的QP值，对所述图像序列进行量化处理，完成图像编码压缩。本发明可以根据图像内容信息进行动态修改量化系数QP的视频动态压缩，完成无线图像传输系统中图像压缩码率的在线更新

JUNO Sensitivity on Proton Decay p→νˉK+p\to \bar\nu K^+ Searches

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this paper, the potential on searching for proton decay in $p\to \bar\nu K^+$ mode with JUNO is investigated.The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits to suppress the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via $p\to \bar\nu K^+$ is 36.9% with a background level of 0.2 events after 10 years of data taking. The estimated sensitivity based on 200 kton-years exposure is $9.6 \times 10^{33}$ years, competitive with the current best limits on the proton lifetime in this channel

JUNO sensitivity on proton decay p → ν K + searches*

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this study, the potential of searching for proton decay in the $p\to \bar{\nu} K^+$ mode with JUNO is investigated. The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits suppression of the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via $p\to \bar{\nu} K^+$ is 36.9% ± 4.9% with a background level of $0.2\pm 0.05({\rm syst})\pm$$0.2({\rm stat})$ events after 10 years of data collection. The estimated sensitivity based on 200 kton-years of exposure is $9.6 \times 10^{33}$ years, which is competitive with the current best limits on the proton lifetime in this channel and complements the use of different detection technologies