Search
Results
-
Model-free Consensus Maximization for Non-Rigid Shapes
(2018)Lecture Notes in Computer Science ~ Computer Vision – ECCV 2018Many computer vision methods use consensus maximization to relate measurements containing outliers with the correct transformation model. In the context of rigid shapes, this is typically done using Random Sampling and Consensus (RANSAC) by estimating an analytical model that agrees with the largest number of measurements (inliers). However, small parameter models may not be always available. In this paper, we formulate the model-free ...Conference Paper -
Incremental Non-Rigid Structure-from-Motion with Unknown Focal Length
(2018)Lecture Notes in Computer Science ~ Computer Vision – ECCV 2018 15th European Conference, Munich, Germany, September 8-14, 2018, Proceedings, Part XIIIThe perspective camera and the isometric surface prior have recently gathered increased attention for Non-Rigid Structure-from-Motion (NRSfM). Despite the recent progress, several challenges remain, particularly the computational complexity and the unknown camera focal length. In this paper we present a method for incremental Non-Rigid Structure-from-Motion (NRSfM) with the perspective camera model and the isometric surface prior with ...Conference Paper -
Dense 3D Regression for Hand Pose Estimation
(2018)2018 IEEE/CVF Conference on Computer Vision and Pattern RecognitionConference Paper