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Ojala, T., Pietikäinen, M. and Harwood, D. (1994) Performance Evaluation of Texture Measures with Classification Based on Kullback Discrimination of Distributions. Proceedings of the 12th IAPR International Conference on Pattern Recognition (ICPR 1994), 1, 582-585. http://dx.doi.org/10.1109/ICPR.1994.576366

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  • 标题: 基于颜色空间纹理融合特征的SOAMST人脸跟踪算法SOAMST Face Tracking Algorithm Based on the Combined Feature of Color Space and Texture

    作者: 周真真, 冯子亮

    关键字: 人脸跟踪, SOAMST, 二阶空间直方图, MBLBP, 颜色直方图Face Tracking, SOAMST, The Second-Order Spatial Histogram, MBLBP, Color Histogram

    期刊名称: 《Journal of Image and Signal Processing》, Vol.5 No.4, 2016-10-14

    摘要: 针对人脸跟踪中存在的人脸目标与背景颜色相似、光照变化对跟踪算法鲁棒性的影响,本文提出基于颜色空间纹理融合特征的SOAMST跟踪算法,将二阶空间直方图代替SOAMST建立目标模型中的颜色直方图,二阶直方图融合了目标颜色信息和颜色的空间分布信息,比传统颜色直方图更具有目标鉴别能力。此外与MBLBP特征进行融合,构建有效的联合直方图建立目标模型。不同场景下的实验结果表明,与原算法比较,本文的改进算法在人脸颜色与背景相似,光照变化,旋转大小变化等复杂环境下,抗干扰性更强,有更好的跟踪效果,具有更高的准确性和鲁棒性。 In view of the existing question that in the human face tracking, face target is similar to the back-ground color, and light changes impact on the robustness of tracking algorithm, in this paper we put forward a SOAMST face tracking algorithm based on the combined feature of color space and texture, which chooses the second-order spatial histogram instead of SOAMST color histogram to build target model. The second-order histogram is combined with color’s information and color spatial distribution’s information, compared to the traditional color histogram with more target identification ability. In addition to the fusion of MBLBP characteristics, it can build effective joint histogram to establish target model. Experimental results in different scenarios show that compared with the original algorithm, the improved algorithm has better anti-interference performance, better tracking effect, and a higher accuracy and robustness under the complex environment which face color is similar to the background, light changes, and the size of the changes.