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Real-Time Recognition of Objectsby Cascading Approximate Nearest Neighbor Searchers

LanguageJapanese
TypeProceedings of Japanese Conferences
AuthorsKazuto NOGUCHI, Takayuki HONDO, Masakazu IWAMURA, Koichi KISE
TitleReal-Time Recognition of Objectsby Cascading Approximate Nearest Neighbor Searchers
JournalProceedings of MIRU 2007
Presentation numberDS-16
Pagespp.467-468
ReviewedNot reviewed
DateJuly 2007
Research fieldsPattern recognition, Object Recognition
KeyNoguchi2007_MIRU_Real (id=986)
MIRU2007 Best Demonstration Award Winner

Abstract

We demonstrate a system for real-time object recognition which employs PCA-SIFT as local descriptors of images. Object recognition based on PCA-SIFT has posed problems of processing time for both extraction and matching of local descriptors because of their large number. To solve the problem about extraction, the proposed system is equipped with a GPU (Graphical Processing Unit). For the problem about matching, we utilize a cascaded approximate nearest neighbor searchers. These two factors enable us real-time object recognition even with a database of 100,000 objects.

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