T
Takeo Kanade
Researcher at Carnegie Mellon University
Publications - 800
Citations - 107709
Takeo Kanade is an academic researcher from Carnegie Mellon University. The author has contributed to research in topics: Motion estimation & Image processing. The author has an hindex of 147, co-authored 799 publications receiving 103237 citations. Previous affiliations of Takeo Kanade include National Institute of Advanced Industrial Science and Technology & Hitachi.
Papers
More filters
Book ChapterDOI
The new generation system for the CMU Navlab
TL;DR: The Carnegie—Mellon University Navigational Laboratory (the CMU Navlab) project integrates sensing, image understanding, planning, control, and software systems architectures onto a self-contained mobile robot.
Journal ArticleDOI
Data-Driven Objectness
TL;DR: A data-driven approach to estimate the likelihood that an image segment corresponds to a scene object (its “objectness”) by comparing it to a large collection of example object regions using 5 million object regions along with their metadata information is proposed.
Proceedings ArticleDOI
Multi-label classification for the analysis of human motion quality
TL;DR: Methods for assessing human motion quality using body-worn tri-axial accelerometers and gyroscopes form the basis for an at-home rehabilitation device that will recognize errors in patient exercise performance, provide appropriate feedback on the performance, and motivate the patient to continue the prescribed regimen.
Proceedings ArticleDOI
3D voxel construction based on epipolar geometry
TL;DR: The concept of projective 3D voxel, which makes it possible to handle 3D geometric data without complete 3D geometry information, is described.
Proceedings ArticleDOI
Filtered Component Analysis to Increase Robustness to Local Minima in Appearance Models
TL;DR: FCA learns an optimal set of filters with which to build a multi-band representation of the object, and was found to be more robust than either grayscale or Gabor filters to problems of local minima.