To achieve online automatic classification of product is a great need of e-commerce de-velopment. By analyzing the characteristics of product images, we proposed a fast supervised image classifier which is based on cl...To achieve online automatic classification of product is a great need of e-commerce de-velopment. By analyzing the characteristics of product images, we proposed a fast supervised image classifier which is based on class-specific Pyramid Histogram Of Words (PHOW) descriptor and Im-age-to-Class distance (PHOW/I2C). In the training phase, the local features are densely sampled and represented as soft-voting PHOW descriptors, and then the class-specific descriptors are built with the means and variances of distribution of each visual word in each labelled class. For online testing, the normalized chi-square distance is calculated between the descriptor of query image and each class-specific descriptor. The class label corresponding to the least I2C distance is taken as the final winner. Experiments demonstrate the effectiveness and quickness of our method in the tasks of product clas-sification.展开更多
针对现有限流设施与策略智能化程度不高,灵活性较差的问题,提出一种基于光流特征描述子的站点限流设施优化方法.首先,根据枢纽内场景特点,设置感兴趣区域(region of interest,ROI),从而降低后续操作的计算量,提高算法的执行效率;然后,...针对现有限流设施与策略智能化程度不高,灵活性较差的问题,提出一种基于光流特征描述子的站点限流设施优化方法.首先,根据枢纽内场景特点,设置感兴趣区域(region of interest,ROI),从而降低后续操作的计算量,提高算法的执行效率;然后,在建立光流特征描述子的基础上,对图片序列进行特征分析;最后,基于人群聚集特征,对经典单分类支持向量机进行调整,并实现超负荷状态的检测.实验结果表明,提出的方法能够对站台人群状态进行准确检测,有效增强限流设施的自动化水平,为轨道交通站点客流组织与管理提供数据支撑和理论依据.展开更多
基金Supported by the Major Funded Project of National Natural Science Foundation of China (No. 70890083)
文摘To achieve online automatic classification of product is a great need of e-commerce de-velopment. By analyzing the characteristics of product images, we proposed a fast supervised image classifier which is based on class-specific Pyramid Histogram Of Words (PHOW) descriptor and Im-age-to-Class distance (PHOW/I2C). In the training phase, the local features are densely sampled and represented as soft-voting PHOW descriptors, and then the class-specific descriptors are built with the means and variances of distribution of each visual word in each labelled class. For online testing, the normalized chi-square distance is calculated between the descriptor of query image and each class-specific descriptor. The class label corresponding to the least I2C distance is taken as the final winner. Experiments demonstrate the effectiveness and quickness of our method in the tasks of product clas-sification.
文摘针对现有限流设施与策略智能化程度不高,灵活性较差的问题,提出一种基于光流特征描述子的站点限流设施优化方法.首先,根据枢纽内场景特点,设置感兴趣区域(region of interest,ROI),从而降低后续操作的计算量,提高算法的执行效率;然后,在建立光流特征描述子的基础上,对图片序列进行特征分析;最后,基于人群聚集特征,对经典单分类支持向量机进行调整,并实现超负荷状态的检测.实验结果表明,提出的方法能够对站台人群状态进行准确检测,有效增强限流设施的自动化水平,为轨道交通站点客流组织与管理提供数据支撑和理论依据.
