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1,322
Behind the Depth Uncertainty: Resolving Ordinal Depth in SFM
"... Abstract. Structure from Motion(SFM) is beset by the noise sensitivity problem. Previous works show that some motion ambiguities are inher-ent and errors in the motion estimates are inevitable. These errors may render accurate metric depth estimate difficult to obtain. However, can we still extract ..."
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Abstract. Structure from Motion(SFM) is beset by the noise sensitivity problem. Previous works show that some motion ambiguities are inher-ent and errors in the motion estimates are inevitable. These errors may render accurate metric depth estimate difficult to obtain. However, can we still extract
Image-Based Rendering of Range Data with Depth Uncertainty By
"... Image-Based Rendering is an exciting new field, which lies in between Computer Graphics and Computer Vision. We believe that the more we use the knowledge from Computer Vision in our graphics rendering algorithms, the better our final rendered images will be. This dissertation presents a framework t ..."
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to identify what information from computer vision is relevant for rendering and how to render it. Instead of only using the depth information per pixel, we compute what we call a depth uncertainty region around it. We show how to compute this region from an existing 3-D recovering algorithm called range
Kalman Filter-based Algorithms for Estimating Depth from Image Sequences
, 1989
"... Using known camera motion to estimate depth from image sequences is an important problem in robot vision. Many applications of depth-from-motion, including navigation and manipulation, require algorithms that can estimate depth in an on-line, incremental fashion. This requires a representation that ..."
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Cited by 259 (26 self)
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that records the uncertainty in depth estimates and a mechanism that integrates new measurements with existing depth estimates to reduce the uncertainty over time. Kalman filtering provides this mechanism. Previous applications of Kalman filtering to depth-from-motion have been limited to estimating depth
The Economic Implications of Corporate Financial Reporting
, 2004
"... We survey 401 financial executives, and conduct in-depth interviews with an additional 20, to determine the key factors that drive decisions related to reported earnings and voluntary disclosure. The majority of firms view earnings, especially EPS, as the key metric for outsiders, even more so than ..."
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Cited by 369 (17 self)
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We survey 401 financial executives, and conduct in-depth interviews with an additional 20, to determine the key factors that drive decisions related to reported earnings and voluntary disclosure. The majority of firms view earnings, especially EPS, as the key metric for outsiders, even more so than
Unified inverse depth parametrization for monocular slam
- In Proceedings of Robotics: Science and Systems
, 2006
"... Abstract—We present a new parametrization for point features within monocular simultaneous localization and mapping (SLAM) that permits efficient and accurate representation of uncertainty during undelayed initialization and beyond, all within the standard extended Kalman filter (EKF). The key conce ..."
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Cited by 197 (19 self)
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Abstract—We present a new parametrization for point features within monocular simultaneous localization and mapping (SLAM) that permits efficient and accurate representation of uncertainty during undelayed initialization and beyond, all within the standard extended Kalman filter (EKF). The key
Bayesian Modeling of Uncertainty in Low-Level Vision
, 1990
"... The need for error modeling, multisensor fusion, and robust algorithms i becoming increasingly recognized in computer vision. Bayesian modeling is a powerful, practical, and general framework for meeting these requirements. This article develops a Bayesian model for describing and manipulating the d ..."
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Cited by 204 (17 self)
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observer motion from sparse depth (range) measurements. In the third application, we use the Bayesian interpretation f regularization to choose the optimal smoothing parameter for interpolation. The uncertainty modeling techniques that we develop, and the utility of these techniques invarious applications
Probabilistic Algorithms in Robotics
- AI Magazine vol
"... This article describes a methodology for programming robots known as probabilistic robotics. The probabilistic paradigm pays tribute to the inherent uncertainty in robot perception, relying on explicit representations of uncertainty when determining what to do. This article surveys some of the progr ..."
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Cited by 199 (6 self)
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of the progress in the field, using in-depth examples to illustrate some of the nuts and bolts of the basic approach. Our central conjecture is that the probabilistic approach to robotics scales better to complex real-world applications than approaches that ignore a robot’s uncertainty. 1
Global and regional climate changes due to black carbon,
- Nat. Geosci.,
, 2008
"... Figure 1: Global distribution of BC sources and radiative forcing. a, BC emission strength in tons per year from a study by Bond et al. Full size image (42 KB) Review Nature Geoscience 1, 221 -227 (2008 Black carbon in soot is the dominant absorber of visible solar radiation in the atmosphere. Ant ..."
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Cited by 228 (5 self)
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. The uncertainty in the published estimates for BC emissions is a factor of two to five on regional scales and at least 50% on global scales. High BC emissions ( Regional hotspots Until about the 1950s, North America and Western Europe were the major sources of soot emissions, but now developing nations
Depth distortion under calibration uncertainty
- COMPUTER VISION AND IMAGE UNDERSTANDING
, 2004
"... ..."
Adaptive Vision based Tracking Control of Robots with uncertainty in Depth Information”,
- Proc. of IEEE Int. Conference on Robotics and Automation,
, 2007
"... Abstract-In this paper, a vision based tracking controller with adaptation to uncertainty in depth information is presented. Depth uncertainty plays a special role in visual tracking as it appears nonlinearly in the overall Jacobian matrix and hence cannot be adapted together with other uncertain k ..."
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Cited by 5 (2 self)
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Abstract-In this paper, a vision based tracking controller with adaptation to uncertainty in depth information is presented. Depth uncertainty plays a special role in visual tracking as it appears nonlinearly in the overall Jacobian matrix and hence cannot be adapted together with other uncertain
Results 1 - 10
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1,322
