Robust Method of Vote Aggregation and Proposition Verification for Invariant Local Features

Grzegorz Kurzejamski, Jacek Zawistowski, Grzegorz Sarwas
2015 Proceedings of the 10th International Conference on Computer Vision Theory and Applications  
This paper presents a method for analysis of the vote space created from the local features extraction process in a multi-detection system. The method is opposed to the classic clustering approach and gives a high level of control over the clusters composition for further verification steps. Proposed method comprises of the graphical vote space presentation, the proposition generation, the two-pass iterative vote aggregation and the cascade filters for verification of the propositions. Cascade
more » ... ilters contain all of the minor algorithms needed for effective object detection verification. The new approach does not have the drawbacks of the classic clustering approaches and gives a substantial control over process of detection. Method exhibits an exceptionally high detection rate in conjunction with a low false detection chance in comparison to alternative methods.
doi:10.5220/0005267002520259 dblp:conf/visapp/KurzejamskiZS15 fatcat:vhklssfnqjedhjs2sxgtn6ltka