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» Probabilistic Object Tracking Using Multiple Features
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ICRA
2010
IEEE
164views Robotics» more  ICRA 2010»
14 years 8 months ago
Boundary detection based on supervised learning
— Detecting the boundaries of objects is a key step in separating foreground objects from the background, which is useful for robotics and computer vision applications, such as o...
Kiho Kwak, Daniel F. Huber, Jeongsook Chae, Takeo ...
CVPR
2007
IEEE
15 years 11 months ago
Image representations beyond histograms of gradients: The role of Gestalt descriptors
Histograms of orientations and the statistics derived from them have proven to be effective image representations for various recognition tasks. In this work we attempt to improve...
Stanley M. Bileschi, Lior Wolf
BMVC
2010
14 years 7 months ago
Reducing mismatching under time-pressure by reasoning about visibility and occlusion
Three methods are explored which help indicate whether feature points are potentially visible or occluded in the matching phase of the keyframe-based real-time visual SLAM system....
Somkiat Wangsiripitak, David W. Murray
ISMAR
2002
IEEE
15 years 2 months ago
Accurate Camera Calibration for Off-line, Video-Based Augmented Reality
Camera tracking is a fundamental requirement for videobased Augmented Reality applications. The ability to accurately calculate the intrinsic and extrinsic camera parameters for e...
Simon Gibson, Jonathan Cook, Toby Howard, Roger J....
RAS
2002
247views more  RAS 2002»
14 years 9 months ago
Reference scan matching for global self-localization
Especially in dynamic environments a key feature concerning the robustness of mobile robot navigation is the capability of global self-localization. This term denotes a robot'...
Joachim Weber, Lutz Franken, Klaus-Werner Jör...