Robust single-view geometry and motion reconstruction
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We introduce a computational framework for discovering regular or repeated geometric structures in 3D shapes. We describe and classify possible regular structures and present an effective algorithm for detecting such repeated geometric patterns in point- o ...
We propose a method for signal reconstruction in semi-parametric dictionaries. The proposed algorithm estimates both the signal decomposition and the intrinsic parameters of the dictionary during the reconstruction process. Theoretical results about the co ...
We propose a method for signal reconstruction in semi-parametric dictionaries. The proposed algorithm estimates both the signal decomposition and the intrinsic parameters of the dictionary during the reconstruction process. Theoretical results about the co ...
We demonstrate how the scale axis transform can be used to compute a parameterized family of shape skeletons. The skeletons gradually represent only the most important features of a shape, in a scale-adaptive manner. Here a shape O is any bounded open subs ...
We propose a method for signal reconstruction in semi-parametric dictionaries. The proposed algorithm estimates both the signal decomposition and the intrinsic parameters of the dictionary during the reconstruction process. Some results about the convergen ...
The level set method is a popular technique for tracking moving interfaces in several disciplines including computer vision and fluid dynamics. However, despite its high flexibility, the original level set method is limited by two important numerical issue ...
Institute of Electrical and Electronics Engineers2012
The switching linear dynamical system (SLDS) is a popular model in time-series analysis. However, the complexity of inferring the state of the latent variables scales exponentially with the length of the time-series, resulting in many approximation strateg ...
Demand has emerged for next generation visual technologies that go beyond conventional 2D imaging. Such technologies should capture and communicate all perceptually relevant three-dimensional information about an environment to a distant observer, providin ...
It is well-known that the Gaussian functions and, more generally, their modulations-translations (the Gabor functions) have the unique property of being optimally localized in space and frequency in the sense of Heisenberg's uncertainty principle. In this ...
In this paper we define a scale-space for cortical mean curvature maps on the sphere, that offers a hierarchical representation of the cortical structures, useful in multi-scale algorithms. A spherical feature map is obtained through inflation of the corti ...
