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
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Patent
System and method for servoing on a moving fixation point within a dynamic scene
TL;DR: In this article, a system and method for servoing on a moving target within a dynamic scene is described, which includes a master variable pointing camera system and a plurality of slave variable pointing cameras positioned around the scene.
Proceedings ArticleDOI
High-zoom video hallucination by exploiting spatio-temporal regularities
TL;DR: The problem of super-resolving a human face video by a very high (/spl times/ 16) zoom factor is considered using a graphical model that encodes, (1) spatio-temporal consistencies, and (2) image formation & degradation processes.
Book ChapterDOI
Adaptive control of space robot system with an attitude controlled base
TL;DR: In this article, an adaptive control of a space robot system with an attitude-controlled base on which the robot is attached is proposed, where most tasks are specified in inertia space, instead of joint space, and two potential problems, unavailability of the joint trajectory (since mapping from inertia space trajectory is dynamics-dependent and subject to uncertainty), and nonlinear parameterization in inertia spaces are identified.
Proceedings ArticleDOI
Robust 3D Head Tracking by Online Feature Registration
Jun-Su Jang,Takeo Kanade +1 more
TL;DR: The proposed method can overcome occlusions and divergence problems, and provides fast recovery after occlusion has ended, while preventing divergence problem which frequently occurs in conventional frame-to-frame tracking methods.
Proceedings ArticleDOI
Vision-Based Kalman Filtering for Aircraft State Estimation and Structure from Motion
TL;DR: A critical, albeit brief, overview of feature point tracking, SFM algorithms and Kalman Filtering as they apply specifically to the state estimation problem for aircraft and features of the methods that are well-suited to aircraft estimation problems are noted.