Basis Technology participated in the TAC Entity-Link task of the Knowledge Base Population track at TAC 2012. We developed a supervised learning approach which produces a single model that is capable of operating across all languages and entity types. Our features are based on the outputs of other models, many of which are unsupervised.
This paper presents a novel multi-frame graph matching algorithm for reliable partial alignments among point clouds. We use this algorithm to stitch frames for 3D environment reconstruction. The idea is to utilize both descriptor similarity and mutual spatial coherency of features existed in multiple frames to match these frames. The proposed multi-frame… (More)