Depth maps taken by the low cost Kinect sensor are often noisy and incomplete. Thus, post-processing for obtaining reliable depth maps is necessary for advanced image and video applications such as object recognition and multi-view rendering. In this paper, we propose adaptive directional filters that fill the holes and suppress the noise in depth maps. Specifically, novel filters whose window ...

T his proposal presents a probabilistic formalism that strives for a real time estimation of depth and 3D motion from monocular images. Given a moving camera equipped with an inertial measurement unit and capturing images of a scene with moving objects, we would like to determine, in real time, the 3D structure of the scene in the field of view of the camera as well as the different 3D motions ...

Handling depth images as a point cloud in a 3D data framework and performing planar segmentation in real-time requires heavy computation and it is a major challenge. Available planar-segmentation algorithms are mostly based on surface normals and/or curvatures, and consequently, do not provide real-time performance. In this abstract paper, we introduce a real-time planar-segmentation method for...

In this note we describe a method for recursively estimating the depth of a scene from a sequence of images. The input to the estimator are brightness values at a number of locations of a grid in a video image, and the output is the relative (scaled) depth corresponding to each image-point. The estimator is invariant with respect to the motion of the viewer, in the sense that the motion paramet...

We propose a novel pipeline for 3D reconstruction from image sequences that solely relies on dense methods. At no point sparse features are required. As input we only need a sequence of color images capturing a static scene while following a continuous path. Furthermore, we assume that an intrinsic camera calibration is known. Our pipeline comprises three steps: (1) First, we jointly estimate c...