Titlebook: Computer Vision -- ECCV 2014; 13th European Confer David Fleet,Tomas Pajdla,Tinne Tuytelaars Conference proceedings 2014 Springer Internati

夜晚

Material Classification Based on Training Data Synthesized Using a BTF Databaseg these variations for material classification. Using synthetic training data created from separately acquired material and illumination characteristics allows to overcome the problems of existing material databases which only include a tiny fraction of the possible real-world conditions under contr

鞠躬

overweight

Transfer Learning Based Visual Tracking with Gaussian Processes Regressionof target appearance as exponentially related to the confidence of a classifier output. By contrast, in this paper we directly analyze this probability using Gaussian Processes Regression (GPR), and introduce a latent variable to assist the tracking decision. Our observation model for regression is

嫌恶

Separable Spatiotemporal Priors for Convex Reconstruction of Time-Varying 3D Point Clouds, or miscorrespondence. We present a statistical model of 3D motion data, based on the Kronecker structure of the spatiotemporal covariance of natural motion, as a prior on 3D motion. This prior is expressed as a matrix normal distribution, composed of separable and compact row and column covariance

interrogate

音乐等

Local Estimation of High Velocity Optical Flow with Correlation Image Sensor, the problem of the optical flow estimation is ill-posed if only the temporal constancy of the image brightness is the valid assumption. When given images are captured by the correlation image sensors, though, you can make the problem of the optical flow estimation well-posed under some condition a

antiquated

Rank Minimization with Structured Data Patternsement matrix are available, the problem can be solved using factorization. However, in the case of missing data no satisfactory solution exists. Recent approaches replace the rank term with the weaker (but convex) nuclear norm. In this paper we show that this heuristic works poorly on problems where

magnanimity

Feckless

智力高

Pipe-Run Extraction and Reconstruction from Point Cloudsive similarities from raw data to guide primitive fitting, increasing robustness to data noise and incompleteness. Finally, . are automatically detected to close gaps and propagate connectivity information. The resulting model is more than a collection of 3D triangles, as it contains semantic labels for pipes as well as their connectivity.