Accurate detection of moving objects is an important step in stable tracking or recognition. By using a nonparametric density estimation method over a joint domain-range representation of image pixels, the correlation...Accurate detection of moving objects is an important step in stable tracking or recognition. By using a nonparametric density estimation method over a joint domain-range representation of image pixels, the correlation between neighboring pixels can be used to achieve high levels of detection accuracy in the presence of dynamic background. However, color similarity between foreground and background will cause many foreground pixels to be misclassified. In this paper, an adaptive foreground model is exploited to detect moving objects in dynamic scenes. The foreground model provides an effective description of foreground by adaptively combining the temporal persistence and spatial coherence of moving objects. Building on the advantages of MAP-MRF (the maximum a posteriori in the Markov random field) decision framework, the proposed method performs well in addressing the challenging problem of missed detection caused by similarity in color between foreground and background pixels. Experimental results on real dynamic scenes show that the proposed method is robust and efficient.展开更多
The neutral hydrogen 21 cm line is potentially a very powerful probe of the observable universe, and a number of on-going experiments are trying to detect it at cosmological distances. However, the presence of strong ...The neutral hydrogen 21 cm line is potentially a very powerful probe of the observable universe, and a number of on-going experiments are trying to detect it at cosmological distances. However, the presence of strong foreground radiations such as the galactic synchrotron radiation, galactic free-free emission and extragalactic radio sources make it a very challenging task.For the design of 21 cm experiments and analysis of their data, simulation is an essential tool, and good sky foreground model is needed. With existing data the whole sky maps are available only in low angular resolutions or for limited patches of sky,which is inadequate in the simulation of these new 21 cm experiments. In this paper, we present the method of constructing a high resolution self-consistent sky model at low frequencies, which incorporates both diffuse foreground and point sources.Our diffuse map is constructed by generating physical foreground components including the galactic synchrotron emission and galactic free-free emission. The point source sample is generated using the actual data from the NRAO VLA Sky Survey(NVSS)and the Sydney University Molonglo Sky Survey(SUMSS) where they are available and complete in flux limit, and mock point sources according to statistical distributions. The entire model is made self-consistent by removing the integrated flux of the point sources from the diffuse map so that this part of radiation is not double counted. We show that with the point sources added, a significant angular power is introduced in the mock sky map, which may be important for foreground subtraction simulations.Our sky maps and point source catalogues are available to download.展开更多
针对户外视频监控存在光照变化这一问题,提出一个用于准确完成目标检测的实时背景建模框架.考虑到目标检测的准确性要求,建立基于帧间像素亮度差统计直方图的像素亮度扰动阈值.在此基础上,针对背景建模的实时性要求,提出一种基于自回归...针对户外视频监控存在光照变化这一问题,提出一个用于准确完成目标检测的实时背景建模框架.考虑到目标检测的准确性要求,建立基于帧间像素亮度差统计直方图的像素亮度扰动阈值.在此基础上,针对背景建模的实时性要求,提出一种基于自回归背景模型的参数快速更新方法.鉴于不同光照变化的适应性要求,定义对光照变化不敏感的背景纹理模型.上述模型统称为自回归–纹理(Auto regression and texture,ART)模型,该模型适应于户外光照变化.基于该模型构建像素亮度和纹理置信区间用于目标检测.实验结果表明,该框架能适应和实时跟踪户外背景的光照变化,并对目标进行准确检测.展开更多
自然场景中的光照突变和树枝、水面等不规则运动是背景建模的主要困难.针对该问题,提出一种分步的融合时域信息和空域信息的背景建模方法.在时域,采用具有光照不变性的颜色空间表征时域信息,并提出对噪声和光照突变具有较好适应性的码...自然场景中的光照突变和树枝、水面等不规则运动是背景建模的主要困难.针对该问题,提出一种分步的融合时域信息和空域信息的背景建模方法.在时域,采用具有光照不变性的颜色空间表征时域信息,并提出对噪声和光照突变具有较好适应性的码字聚类准则和自适应背景更新策略,构造了对噪声和光照突变具有较好适应性的时域信息背景模型.在空域,通过采样将测试序列图像分成两幅子图,而后利用时域模型检测其中一幅子图,并将检测结果作为另一幅子图的先验信息,同时采用马尔科夫随机场(Markov random field,MRF)对其加以约束,最终检测其状态.在多个测试视频序列上的实验结果表明,本文背景模型对于自然场景中的光照突变和不规则运动具有较好的适应性.展开更多
基金Project (Nos 60602012 and 60675023) supported by the National Natural Science Foundation of Chinathe National High-Tech Re-search and Development Program (863) of China (No 2007AA01Z 164)the Shanghai Key Laboratory Opening Plan Grant (No.06dz22103),China
文摘Accurate detection of moving objects is an important step in stable tracking or recognition. By using a nonparametric density estimation method over a joint domain-range representation of image pixels, the correlation between neighboring pixels can be used to achieve high levels of detection accuracy in the presence of dynamic background. However, color similarity between foreground and background will cause many foreground pixels to be misclassified. In this paper, an adaptive foreground model is exploited to detect moving objects in dynamic scenes. The foreground model provides an effective description of foreground by adaptively combining the temporal persistence and spatial coherence of moving objects. Building on the advantages of MAP-MRF (the maximum a posteriori in the Markov random field) decision framework, the proposed method performs well in addressing the challenging problem of missed detection caused by similarity in color between foreground and background pixels. Experimental results on real dynamic scenes show that the proposed method is robust and efficient.
基金supported by the National Natural Science Foundation of Guangdong (Grant No. U1501501)the Ministry of Science and Technology (Grant No. 2016YFE0100300)+2 种基金the National Natural Science Foundation of China (Grant Nos. 11473044, 11761141012, 11633004, and 11653003)the Chinese Academy of Sciences (Grant No. QYZDJ-SSWSLH017)the support by the China Scholarship Council Cai Yuanpei Grant
文摘The neutral hydrogen 21 cm line is potentially a very powerful probe of the observable universe, and a number of on-going experiments are trying to detect it at cosmological distances. However, the presence of strong foreground radiations such as the galactic synchrotron radiation, galactic free-free emission and extragalactic radio sources make it a very challenging task.For the design of 21 cm experiments and analysis of their data, simulation is an essential tool, and good sky foreground model is needed. With existing data the whole sky maps are available only in low angular resolutions or for limited patches of sky,which is inadequate in the simulation of these new 21 cm experiments. In this paper, we present the method of constructing a high resolution self-consistent sky model at low frequencies, which incorporates both diffuse foreground and point sources.Our diffuse map is constructed by generating physical foreground components including the galactic synchrotron emission and galactic free-free emission. The point source sample is generated using the actual data from the NRAO VLA Sky Survey(NVSS)and the Sydney University Molonglo Sky Survey(SUMSS) where they are available and complete in flux limit, and mock point sources according to statistical distributions. The entire model is made self-consistent by removing the integrated flux of the point sources from the diffuse map so that this part of radiation is not double counted. We show that with the point sources added, a significant angular power is introduced in the mock sky map, which may be important for foreground subtraction simulations.Our sky maps and point source catalogues are available to download.
文摘针对户外视频监控存在光照变化这一问题,提出一个用于准确完成目标检测的实时背景建模框架.考虑到目标检测的准确性要求,建立基于帧间像素亮度差统计直方图的像素亮度扰动阈值.在此基础上,针对背景建模的实时性要求,提出一种基于自回归背景模型的参数快速更新方法.鉴于不同光照变化的适应性要求,定义对光照变化不敏感的背景纹理模型.上述模型统称为自回归–纹理(Auto regression and texture,ART)模型,该模型适应于户外光照变化.基于该模型构建像素亮度和纹理置信区间用于目标检测.实验结果表明,该框架能适应和实时跟踪户外背景的光照变化,并对目标进行准确检测.
文摘自然场景中的光照突变和树枝、水面等不规则运动是背景建模的主要困难.针对该问题,提出一种分步的融合时域信息和空域信息的背景建模方法.在时域,采用具有光照不变性的颜色空间表征时域信息,并提出对噪声和光照突变具有较好适应性的码字聚类准则和自适应背景更新策略,构造了对噪声和光照突变具有较好适应性的时域信息背景模型.在空域,通过采样将测试序列图像分成两幅子图,而后利用时域模型检测其中一幅子图,并将检测结果作为另一幅子图的先验信息,同时采用马尔科夫随机场(Markov random field,MRF)对其加以约束,最终检测其状态.在多个测试视频序列上的实验结果表明,本文背景模型对于自然场景中的光照突变和不规则运动具有较好的适应性.
