Falls are one of the major risks for seniors living alone at home. Computer vision systems, which do not require to wear sensors, offer a new and promising solution for fall detection. In this work, an occlusion robust method is presented based on two features: human centroid height relative to the ground and body velocity. Indeed, the first feature is an efficient solution to detect falls as t...

We present a novel algorithm for image-based surface reconstruction from a set of calibrated images. The problem is formulated in Bayesian framework, where estimates of depth and visibility in a set of selected cameras are iteratively improved. The core of the algorithm is the minimisation of overall geometric L2 error between measured 3D points and the depth estimates. In the visibility estima...

Reliable depth estimation is important to many autonomous robotic systems and visual control algorithms. The Microsoft Kinect is a new, low cost game controller peripheral that calculates a depth map of the environment with good accuracy and high rate. In this paper we use the calibrated output of the depth sensor to obtain an accurate absolute depth map. Subsequently by using a Randomized Houg...

The multi-view plus depth (MVD) format is a promising representation approach for 3D and free viewpoint video systems as it allows synthesizing more views at the decoder than those explicitly coded at the encoder. This format represents each view of a visual scene with both texture (array of color pixels) and a depth map which provides information about the 3D scene geometry. Thus, for the tran...

Focus fusion methods combine a set of images focused at different depths into a single image where all parts are in focus. The quality of the fusion result strongly depends on a decision map that determines the in-focus areas. Most approaches in the literature achieve this by local decisions without explicitly enforcing smoothness of the depth map. The goal of our paper is to introduce a modern...

A novel dense depth map estimation algorithm is proposed in order to meet the requirements of N-view plus N-depth representation, which is one of the standardization efforts for the upcoming 3D display technologies. Hence, extraction of multiple depth maps is achieved from multi-view video. Starting from the piecewise planarity assumption of the scene, estimation of 3D structure of the patches,...

Depth information is essential for depth image-based rendering (DIBR), which is one of the rendering processes for the virtual view using a color image and its corresponding depth map. Although there are several depth estimation methods, more accurate depth estimation is still required. Since inaccurate depth information along object boundaries causes serious rendering errors, depth boundary in...

The RGB-D cameras have enjoined a great popularity these years. However, the quality of the depth maps obtained by such cameras is far from perfect. In this paper, we propose a framework for shape preserving depth map restoration for RGB-D cameras. The quality of the depth map is improved from three aspects: 1) the proposed region adaptive bilateral filter (RA-BF) smooths the depth noise across...

The ongoing success of three-dimensional (3D) cinema fuels increasing efforts to spread the commercial success of 3D to new markets. The possibilities of a convincing 3D experience at home, such as three-dimensional television (3DTV), has generated a great deal of interest within the research and standardization community. A central issue for 3DTV is the creation and representation of 3D conten...

The depth map captured by sensors (e.g., the time of flight (ToF) and Kinect) is often prone to low resolution, degradation, noise, poor quality. This paper proposes a novel model for robust estimation RGB-D images through local nonlocal manifold regularizations. first stage called deep prior (DDPM), inspired partly (DDP) model, that convolutional neural network (CNN) integrated with regulariza...