Physical Sciences and Mathematics Commons^™

Semi-Supervised Hashing With Semantic Confidence For Large Scale Visual Search, Yingwei Pan, Ting Yao, Houqiang Li, Chong-Wah Ngo, Tao Mei

Research Collection School Of Computing and Information Systems

Similarity search is one of the fundamental problems for large scale multimedia applications. Hashing techniques, as one popular strategy, have been intensively investigated owing to the speed and memory efficiency. Recent research has shown that leveraging supervised information can lead to high quality hashing. However, most existing supervised methods learn hashing function by treating each training example equally while ignoring the different semantic degree related to the label, i.e. semantic confidence, of different examples. In this paper, we propose a novel semi-supervised hashing framework by leveraging semantic confidence. Specifically, a confidence factor is first assigned to each example by neighbor …