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» Quantifying Ambiguities in Inferring Vector-Based 3D Models
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BMVC
2000
13 years 6 months ago
Quantifying Ambiguities in Inferring Vector-Based 3D Models
This paper presents a framework for directly addressing issues arising from self-occlusions and ambiguities due to the lack of depth information in vector-based representations. V...
Eng-Jon Ong, Shaogang Gong
3DPVT
2006
IEEE
188views Visualization» more  3DPVT 2006»
13 years 8 months ago
Statistical Inference of Biological Structure and Point Spread Functions in 3D Microscopy
We present a novel method for detecting and quantifying 3D structure in stacks of microscopic images captured at incremental focal lengths. We express the image data as stochastic...
Joseph Schlecht, Kobus Barnard, Barry Pryor
ICPR
2002
IEEE
13 years 9 months ago
3D Tracking of Human Locomotion: A Tracking as Recognition Approach
Estimating mode (walking/running/standing) and phases of human locomotion is important for video understanding. We present a new ”tracking as recognition” approach. A hierarch...
Tao Zhao, Ramakant Nevatia
CVPR
2006
IEEE
14 years 7 months ago
A Dynamic Bayesian Network Model for Autonomous 3D Reconstruction from a Single Indoor Image
When we look at a picture, our prior knowledge about the world allows us to resolve some of the ambiguities that are inherent to monocular vision, and thereby infer 3d information...
Erick Delage, Honglak Lee, Andrew Y. Ng
ICCV
2009
IEEE
14 years 10 months ago
Quantifying Contextual Information for Object Detection
Context is critical for minimising ambiguity in object de- tection. In this work, a novel context modelling framework is proposed without the need of any prior scene segmen- tat...
Wei-Shi Zheng, Shaogang Gong and Tao Xiang