Encoding Optimization Using Nearest Neighbor Descriptor

摘要：

　　The Bag-of-words framework is probably one of the best models used in image classification.In this model,coding plays a very important role in the classification process.There are many coding methods that have been proposed to encode images in different ways.The relationship between different codewords is studied,but the relationship among descriptors is not fully discovered.In this work,we aim to draw a relationship between descriptors,and propose a new method that can be used with other coding methods to improve the performance.The basic idea behind this is encoding the descriptor not only with its nearest codewords but also with the codewords of its nearest neighboring descriptors.Experiments on several benchmark datasets show that even using this simple relationship between the descriptors helps to improve coding methods.

关键词： Nearest neighbor descriptor Group saliency coding Soft coding Local constraint linear coding

作者: Muhammad Rauf Yongzhen Huang Liang Wang

作者单位: National Lab of Pattern Recognition,Institute of Automation,Chinese Academy of Sciences,Beijing 100190,China

会议类型: 国际会议

会议名称: Chinese Conference on Pattern Recognition, CCPR(2014年全国模式识别学术会议)

会议地点: 长沙

会议语种:英文

页码: 81-88

在线出版日期: 2014-11-01（万方平台首次上网日期，不代表论文的发表时间）