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	PKU-ICST at TRECVID 2009: High level feature extraction and search
	Peng, Yuxin ; Yang, Zhiguo ; Cao, Lei ; Yi, Jian ; Wan, Ning ; Feng, Yuan ; Zhai, Xiaohua ; Shi, En ; Li, Hao
	2009
英文摘要	We participate in two tasks of TRECVID 2009: high-level feature extraction (HLFE) and search. This paper presents our approaches and results in the two tasks. In HLFE task, we mainly focus on exploring the effective feature representation, data imbalance learning and fusion between different data sets. In feature representation, we adopt five basic visual features and six keypoint-based BoW features, and combine them to represent each keyframe image. In imbalance learning, we propose two methods for this problem: OnUm and concept category. In the fusion between different data sets, we use three different training sets: (1) TRECVID 2009 training data set (Tv09), (2) TRECVID 2005 training data set (Tv05), and (3) Flickr images. In search task, we participate in two types of search tasks: automatic search and manual search. We explore multimodal feature representation, which includes visual-based features, concept-based feature, audio features and face features. Based on these features, two retrieval methods are jointly adopted for search task: pair-wise similarity measure and learning-based ranking. We achieve the good results in both tasks. In HLFE task, official evaluation shows that our team ranks 2nd in type A and 1st in types C, a and c. In Search task, official evaluations show that our team rank 2nd in automatic search and 1st in manual search.; EI; 0
语种	英语
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/321460]
专题	计算机科学技术研究所
推荐引用方式 GB/T 7714	Peng, Yuxin,Yang, Zhiguo,Cao, Lei,et al. PKU-ICST at TRECVID 2009: High level feature extraction and search. 2009-01-01.

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