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Scale-invariant feature transform
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#	Item
81	Spatial Priors for Part-Based Recognition using Statistical Models David Crandall1 Cornell University [removed] Pedro Felzenszwalb Add to Reading List Source URL: vision.soic.indiana.edu Language: English - Date: 2014-08-03 00:38:07 Image processing Artificial intelligence Estimation theory Object recognition Maximum likelihood Edge detection One-shot learning Scale-invariant feature transform Computer vision Vision Imaging
82	Microsoft Word - ICPR08_Final.docx Add to Reading List Source URL: graphics.usc.edu Language: English - Date: 2008-10-03 14:29:34 Feature detection Scale space Feature Object recognition SURF Visual descriptors Principal component analysis GLOH Histogram of oriented gradients Computer vision Artificial intelligence Scale-invariant feature transform
83	The Gixel Array Descriptor (GAD) for Multi-Modal Image Matching Guan Pang University of Southern California Ulrich Neumann University of Southern California Add to Reading List Source URL: graphics.usc.edu Language: English - Date: 2013-02-03 21:17:18 Optics Scale-invariant feature transform GLOH Object recognition SURF Visual descriptors Shape context Feature Histogram of oriented gradients Computer vision Vision Imaging
84	Microsoft Word - Augmentedl Exhibitions Using Natural Features_JM.doc Add to Reading List Source URL: graphics.usc.edu Language: English - Date: 2007-10-31 12:46:16 Imaging Object recognition Augmented reality Pose Kernel Motion estimation Affine transformation 3D single object recognition Scale-invariant feature transform Computer vision Vision Geometry
85	Training-based Object Recognition in Cluttered 3D Point Clouds Guan Pang Department of Computer Science University of Southern California Los Angeles, CA, USA [removed] Add to Reading List Source URL: graphics.usc.edu Language: English - Date: 2013-07-23 02:24:33 Optics 3D single object recognition 3D scanner Object recognition Haar-like features 3D modeling Hough transform Photogrammetry Scale-invariant feature transform Computer vision Vision Imaging
86	EXPLORE MULTIPLE CLUES FOR URBAN IMAGES MATCHING Quan Wang, Suya You Computer Science Department University of Southern California Los Angeles, California, U.S.A. ABSTRACT Add to Reading List Source URL: graphics.usc.edu Language: English - Date: 2010-10-29 19:44:14 Artificial intelligence Feature detection Edge detection Feature Canny edge detector Image gradient Histogram of oriented gradients Scale-invariant feature transform Computer vision Image processing Vision
87	Spatial Priors for Part-Based Recognition using Statistical Models David Crandall1 Cornell University [removed] Pedro Felzenszwalb Add to Reading List Source URL: www.cs.cornell.edu Language: English - Date: 2005-04-11 14:45:39 Image processing Artificial intelligence Estimation theory Object recognition Maximum likelihood Edge detection One-shot learning Scale-invariant feature transform Computer vision Vision Imaging
88	MAV Urban Localization from Google Street View Data Andr´as L. Majdik, Yves Albers-Schoenberg, Davide Scaramuzza Abstract— We tackle the problem of globally localizing a camera-equipped micro aerial vehicle flying wit Add to Reading List Source URL: rpg.ifi.uzh.ch Language: English - Date: 2013-08-07 10:17:08 Imaging Scale-invariant feature transform Object recognition Algorithm RANSAC Google Computer vision Statistics Vision
89	• Toyon Research Corporation – A small business with over twenty years of experience in information analysis, simulation, and video processing algorithm development – Offices in Santa Barbara, Add to Reading List Source URL: www.iarpa.gov Language: English - Date: 2014-03-06 18:49:29 3D computer graphics Optics Computer vision 3D modeling 3D scanner Scale-invariant feature transform Imaging Visual effects Vision
90	Online Self-Supervised Segmentation of Dynamic Objects Vitor Guizilini and Fabio Ramos Australian Centre for Field Robotics, School of Information Technologies University of Sydney, Australia {v.guizilini;f.ramos}@acfr.u Add to Reading List Source URL: www-personal.acfr.usyd.edu.au Language: English - Date: 2015-01-05 23:35:35 Segmentation Scale-invariant feature transform Kalman filter RANSAC Matrix Supervised learning Optical flow Determining the number of clusters in a data set Statistics Machine learning Image processing

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