Research Group on Visual Computation

Active projects


Project iconPose Estimation from Line Correspondences
We propose a novel method to compute the absolute pose of a camera system based on straight lines, which are common in urban environment. Since modern cameras are frequently equipped with various location and orientation sensors, we assume that the vertical direction (e.g. a gravity vector) is available. Therefore we formulate the problem in terms of 4 unknowns using 3D line - projection plane correspondences which yields a closed form solution. The solution can be used as a minimal solver as well as a least squares solver without reformulation.
Project iconFilling Missing Parts of a 3D Mesh by Fusion of Incomplete 3D Data
In this work we deal with the problem of fusing different (potentially partial) 3D meshes to fill in missing parts (holes) of an accurate reference 3D model using a less accurate but more complete moving 3D model. Each hole in the partial model is filled from the more complete but less accurate 3D mesh by gradually estimating local affine transformations around the hole's boundary and propagating it into the inner part. Experimental validation is done on a large real dataset, which confirms the accuracy and reliability of the proposed algorithm.
Project iconCorrespondences between Planar Image Patches
We focus on establishing matches between images of urban scenes which are typically composed of planar surface patches with highly repetitive structures. The basic idea of our approach is to formulate the correspondence problem in terms of homography estimation between planar image regions.
Project iconCalibration of Ad-Hoc Camera Networks
An automatic camera network calibration algorithm is proposed. Our aim is to solve the relative pose problem with respect to a 3D planar surface and create a coordinate-system having a camera independent origin.
Project iconVision Graphs - Collaborative Compositing and View Construction
This work is about local processing of photos and associated sensor information on mobile devices, laying the foundations of a collaborative multi-user framework where ad-hoc device groups can share their data around a geographical location to produce more complex composited views of the area, without the need of a cloud-based back-end.
Project iconCalibration of Omnidirectional, Perspective and Lidar Camera Systems
Automatic calibration of ominidirectional, perspective camera and lidar images is important for 3D model construction, robot navigation and environment mapping. The proposed methodology is without any specific constraint on source of data and the calibration can be performed using a single pair of lidar-camera image without any implicit correspondence between image points.
Project iconCollaborative Stereo Reconstruction of Planar Patches
We proposed a pipeline that utilizes an ad-hoc network of camera equipped smartphones in a collaborative manner. The reconstruction is based on segmented planar regions which is especially suitable for scenes having large (near) planar parts. The perspective distortion of a planar region in two views makes it possible to compute the normal and distance of the region w.r.t the world coordinate system.
Project iconEvaluation of Point Matching Methods for Wide-baseline Stereo Correspondence on Mobile Platforms
We carried out quantitative comparison of the most important keypoint detectors and descriptors in the context of wide baseline stereo matching. We found that for resolution of 2 megapixels images the current mobile hardware is capable of providing results efficiently.
Project iconElastic Registration of 3D Objects
Correspondance-less alignment of 3D non-rigid objects using parametric nonlinear deformation models. Our algorithms are able to estimate the parameters of the deformation without an established set of correspondences, thus providing a fully automatic and computationally efficient registration framework for 3D objects.
Project iconExtraction of Near Circular Objects using Markov Random Fields: The Multilayer 'Gas of Circles' Model
A multi-layer binary Markov random field model for extracting an unknown number of possibly touching or overlapping near-circular objects.

Mini Workshop on 3D Data Sensing and Processing...

2017-06-12


Our research project is funded by NKFIH OTKA for Dec 2016 - Nov 2020...

2016-12-16