In this paper, we propose MonoRec, a semi-supervised monocular dense reconstruction architecture that predicts depth maps from a single moving camera in dynamic environments. MonoRec is based on a multi-view stereo setting which encodes the …
In this paper we propose a framework for integrating map-based relocalization into online direct visual odometry. To achieve map-based relocalization for direct methods, we integrate image features into Direct Sparse Odometry (DSO) and rely on …
In this paper we present a sensor fusion framework for the detection and classification of objects in autonomous driving applications. The presented method uses a state-of-the-art convolutional neural network (CNN) to detect and classify object from …
This paper presents a method to calculate a totally focussed colour image from recordings of a plenoptic camera. The three colour channels have to be extracted from the raw image. The virtual depth is estimated analyzing the disparities of image …
We propose a novel direct visual odometry algorithm formicro-lens-array-based light field cameras. The algorithm calculates adetailed, semi-dense 3D point cloud of its environment. Thisis achievedby establishing probabilistic depth hypotheses based …
In this paper we present a new calibration approach for focused plenoptic cameras. We derive a new mathematical projection model of afocused plenoptic camera which considers lateral as well as depth distortion. Therefore, we derive a new depth …
This paper presents a mathematical projection model for focused plenoptic cameras. The model defines the projection from object space to the virtual image space inside the plenoptic camera. We estimate the camera model by performing bundle adjustment …
This paper presents a method to calculate the depth values of 3D points by means of a plenoptic camera. Opposed to other approaches which use the totally focused image to detect points, we operate directly on the micro images taking thus advantage of …