Virtually augmenting hundreds of real pictures: An approach based on learning, retrieval, and tracking

Julien Pilet, Hideo Saito

研究成果: Conference contribution

29 被引用数 (Scopus)


Tracking is a major issue of virtual and augmented reality applications. Single object tracking on monocular video streams is fairly well understood. However, when it comes to multiple objects, existing methods lack scalability and can recognize only a limited number of objects. Thanks to recent progress in feature matching, state-of-the-art image retrieval techniques can deal with millions of images. However, these methods do not focus on real-time video processing and can not track retrieved objects. In this paper, we present a method that combines the speed and accuracy of tracking with the scalability of image retrieval. At the heart of our approach is a bi-layer clustering process that allows our system to index and retrieve objects based on tracks of features, thereby effectively summarizing the information available on multiple video frames. As a result, our system is able to track in real-time multiple objects, recognized with low delay from a database of more than 300 entries.

ホスト出版物のタイトルVR 2010 - IEEE Virtual Reality 2010, Proceedings
出版ステータスPublished - 2010
イベントIEEE Virtual Reality 2010, VR 2010 - Waltham, MA, United States
継続期間: 2010 3 202010 3 24


名前Proceedings - IEEE Virtual Reality


OtherIEEE Virtual Reality 2010, VR 2010
国/地域United States
CityWaltham, MA

ASJC Scopus subject areas

  • 工学(全般)


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