In this paper, we present a novel and efficient scheme for extracting, indexing and retrieving color images. Our motivation was to reduce the space overhead of partition-based approaches taking advantage of the fact t...In this paper, we present a novel and efficient scheme for extracting, indexing and retrieving color images. Our motivation was to reduce the space overhead of partition-based approaches taking advantage of the fact that only a relatively low number of distinct values of a particular visual feature is present in most images. To extract color feature and build indices into our image database we take into consideration factors such as human color perception and perceptual range, and the image is partitioned into a set of regions by using a simple classifying scheme. The compact color feature vector and the spatial color histogram, which are extracted from the seqmented image region, are used for representing the color and spatial information in the image. We have also developed the region-based distance measures to compare the similarity of two images. Extensive tests on a large image collection were conducted to demonstrate the effectiveness of the proposed approach.展开更多
针对视频多目标跟踪中由于目标间的遮挡、交错或目标漂移而导致跟踪失败的情况,提出一种基于卡尔曼滤波以及空间颜色直方图的遮挡预测跟踪算法。利用空间颜色直方图对目标进行建模,可以对不同目标进行区分进而在目标之间出现交错或目标...针对视频多目标跟踪中由于目标间的遮挡、交错或目标漂移而导致跟踪失败的情况,提出一种基于卡尔曼滤波以及空间颜色直方图的遮挡预测跟踪算法。利用空间颜色直方图对目标进行建模,可以对不同目标进行区分进而在目标之间出现交错或目标漂移时仍能跟踪到目标。通过卡尔曼滤波算法可以预测目标的状态,对预测位置之间存在交错的目标进行遮挡标记,以便在下一帧中仍然可以跟踪到被遮挡的目标。采用2D MOT 2015数据集进行实验,跟踪的平均精度达到了34.1%。实验结果表明,所提方法对多目标跟踪的效果有所提高。展开更多
在传统的颜色相关直方图基础上,提出了一种基于空间和颜色自相关的直方图目标检测算法(Spatial and Color Co-occurrence Histogramms,SCCH),该方法采用符合人眼感知的HSV颜色空间,并对其进行非均匀量化,使其更加符合人类生理机制;SCCH...在传统的颜色相关直方图基础上,提出了一种基于空间和颜色自相关的直方图目标检测算法(Spatial and Color Co-occurrence Histogramms,SCCH),该方法采用符合人眼感知的HSV颜色空间,并对其进行非均匀量化,使其更加符合人类生理机制;SCCH算法强调颜色过渡区域的重要性,选取边缘点作为计算对象,同时利用颜色自相关直方图,减少计算量,大大提高了检测效率。展开更多
文摘In this paper, we present a novel and efficient scheme for extracting, indexing and retrieving color images. Our motivation was to reduce the space overhead of partition-based approaches taking advantage of the fact that only a relatively low number of distinct values of a particular visual feature is present in most images. To extract color feature and build indices into our image database we take into consideration factors such as human color perception and perceptual range, and the image is partitioned into a set of regions by using a simple classifying scheme. The compact color feature vector and the spatial color histogram, which are extracted from the seqmented image region, are used for representing the color and spatial information in the image. We have also developed the region-based distance measures to compare the similarity of two images. Extensive tests on a large image collection were conducted to demonstrate the effectiveness of the proposed approach.
文摘针对视频多目标跟踪中由于目标间的遮挡、交错或目标漂移而导致跟踪失败的情况,提出一种基于卡尔曼滤波以及空间颜色直方图的遮挡预测跟踪算法。利用空间颜色直方图对目标进行建模,可以对不同目标进行区分进而在目标之间出现交错或目标漂移时仍能跟踪到目标。通过卡尔曼滤波算法可以预测目标的状态,对预测位置之间存在交错的目标进行遮挡标记,以便在下一帧中仍然可以跟踪到被遮挡的目标。采用2D MOT 2015数据集进行实验,跟踪的平均精度达到了34.1%。实验结果表明,所提方法对多目标跟踪的效果有所提高。
文摘在传统的颜色相关直方图基础上,提出了一种基于空间和颜色自相关的直方图目标检测算法(Spatial and Color Co-occurrence Histogramms,SCCH),该方法采用符合人眼感知的HSV颜色空间,并对其进行非均匀量化,使其更加符合人类生理机制;SCCH算法强调颜色过渡区域的重要性,选取边缘点作为计算对象,同时利用颜色自相关直方图,减少计算量,大大提高了检测效率。