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CRV
2005
IEEE
103views Robotics» more  CRV 2005»
13 years 11 months ago
A Quantitative Comparison of 4 Algorithms for Recovering Dense Accurate Depth
: We report on 4 algorithms for recovering dense depth maps from long image sequences, where the camera motion is known a priori. All methods use a Kalman filter to integrate inte...
Baozhong Tian, John L. Barron
ECCV
2010
Springer
13 years 10 months ago
Analyzing Depth from Coded Aperture Sets
Computational depth estimation is a central task in computer vision and graphics. A large variety of strategies have been introduced in the past relying on viewpoint variations, de...
ICRA
1994
IEEE
89views Robotics» more  ICRA 1994»
13 years 9 months ago
Computation of Shape Through Controlled Active Exploration
Accurate knowledge of depth continues to be of critical importance in robotic systems. Without accurate depth knowledge, tasks such as inspection, tracking, grasping, and collisio...
Christopher E. Smith, Nikolaos Papanikolopoulos
ECCV
2008
Springer
14 years 7 months ago
Flexible Depth of Field Photography
The range of scene depths that appear focused in an image is known as the depth of field (DOF). Conventional cameras are limited by a fundamental trade-off between depth of field a...
Hajime Nagahara, Sujit Kuthirummal, Changyin Zhou,...
ECCV
2002
Springer
14 years 7 months ago
Learning Shape from Defocus
We present a novel method for inferring three-dimensional shape from a collection of defocused images. It is based on the observation that defocused images are the null-space of ce...
Paolo Favaro, Stefano Soatto