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Object recognition / 3D single object recognition / Scale-invariant feature transform / Pose / SURF / Pattern recognition / Hough transform / Bag of words model in computer vision / Computer vision / Vision / Imaging


Local Feature View Clustering for 3D Object Recognition David G. Lowe Computer Science Department University of British Columbia Vancouver, B.C., V6T 1Z4, Canada [removed]
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Document Date: 2001-09-16 01:33:24


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City

Corfu / /

Company

Cambridge University Press / MIT Press / /

Country

Puerto Rico / Canada / Greece / /

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Facility

Object Recognition David G. Lowe Computer Science Department University of British Columbia Vancouver / Fort Collins / /

IndustryTerm

pose solutions / approximate nearest-neighbour search / k-d tree algorithm / on-line learning / 3D solution / real-world object recognition systems / geometric solution / final least-squares solution / pose solution / constrained solution / using approximate nearest-neighbour search / /

Organization

Cambridge University / MIT / 3D Object Recognition David G. Lowe Computer Science Department University / Natural Sciences and Engineering Research Council of Canada / Institute for Robotics and Intelligent Systems of the Networks of Centres / University of British Columbia / /

Person

Krystian Mikolajczyk / Matthew Brown / Jim Little / Shimon / Stephen Se / James L. Crowley / David G. Lowe / Cordelia Schmid / Ronen Basri / Jeff / Hiroshi / Shree K. Nayar / /

Position

Prime Minister / Hilton Head / /

ProvinceOrState

South Carolina / Hawaii / Massachusetts / /

PublishedMedium

Current Opinion / /

Technology

k-d tree algorithm / /

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