Searching for authors named "Takeo Kanade" – sorted by Relevance.
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Computer Vision as a Physical Science
- 14 Cpmputer Vision Physical Science Takeo Kanade 14.1 Introduction In CPlU Ccanp uter Science: a
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On the Source of Asymmetry in Image Registration Problems. Robotics Institute
- ˇglu and Takeo Kanade The Robotics Institute Carnegie Mellon University Pittsburgh, PA 15232 Abstract. Most image
- Cited by 2 (2 self) – Add To MetaCart
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Virtualized Reality: Concepts and Early Results
- of watch- Virtualized Reality: Concepts and Early Results Takeo Kanade, P. J. Narayanan, Peter W. Rander
- Cited by 47 (3 self) – Add To MetaCart
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A Papaperspective Factorization Method for Shape and Motion Recovery
- In this paper, we present a method for recovering both the shape of an object and its motion relative to the camera from a sequence of images of the object, using feature points tracked throughout the sequence. The method is based on the factorization method developed by Tomasi & Kanade, which ac
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Creating 3D Models with Uncalibrated Cameras
- proposed a projective factorization method in [17] which re- Mei Han Takeo Kanade Robotics Institute
- Cited by 12 (1 self) – Add To MetaCart
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Noncontact Visual Three-Dimensional Ranging Devices
- .C. Noncontact visual three-dimensional ranging devices Takeo Kanade, Haruhiko Asada Robotics Institute, Carnegie
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Scene Reconstruction from Multiple Uncalibrated Views
- Scene Reconstruction from Multiple Uncalibrated Views Mei Han Takeo Kanade January 2000 CMU
- Cited by 3 (0 self) – Add To MetaCart
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Robust Subspace Clustering by Combined Use of kNND Metric and SVD Algorithm
- Robust Subspace Clustering by Combined Use of kNND Metric and SVD Algorithm Qifa Ke and Takeo
- Cited by 5 (0 self) – Add To MetaCart
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T.: Robust L1 norm factorization in the presence of outliers and missing data by alternative convex programming
- Programming Qifa Ke and Takeo Kanade Computer Science Department, Carnegie Mellon University, Pittsburgh, PA
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A VLSI Sorting Image Sensor: Global Massively Parallel Intensity-to-Time Processing for Low-Latency Adaptive Vision
- Vladimir Brajovic, Member, IEEE, and Takeo Kanade, Fellow, IEEE Abstract—This paper presents a new
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