Depth from defocus (DFD) is a 3D recovery method based on estimating the amount of defocus induced by finite lens apertures. Given two images with different camera settings, the ...
Scott McCloskey, Michael S. Langer, Kaleem Siddiqi
This paper proposes a fast 3D reconstruction approach for efficiently generating watertight 3D models from multiple short baseline views. Our method is based on the combination of...
Mario Sormann, Christopher Zach, Joachim Bauer, Ko...
Depth ordering is instrumental for understanding the 3D geometry of an image. We as humans are surprisingly good ordering even with abstract 2D line drawings. In this paper we pro...
Zhaoyin Jia, Andrew C. Gallagher, Yao-Jen Chang, T...
In this paper, we propose a novel method for fast nearest neighbors retrieval in non-Euclidean and non-metric spaces. We organize the data into a hierarchical fashion that preserv...
This paper presents a fast, accurate, and novel method for the problem of estimating the number of humans and their positions from background differenced images obtained from a si...
Lan Dong, Vasu Parameswaran, Visvanathan Ramesh, I...