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In recent years, automation becomes more and more important in the world. Autonomous car is an example in our life around. It uses the 3D LiDAR to receive the surrounding information. Then this paper uses 3D LiDAR to capture the environment data to perform the object recognition, motion estimation and path planning to let car auto-drive on the road.
In this paper, a method that directly estimates motion parameters of a range image sensor using range images and optical flow of color images is proposed. Linear equations for motion parameters are introduced by utilizing optical flow. A three-dimensional (3D) map is constructed by registration of range images between frames using the estimated motion parameters. Experiments to construct a 3D map...
The acquisition of surface material properties and lighting conditions is a fundamental step for photo-realistic Augmented Reality (AR). In this paper, we present a new method for the estimation of diffuse and specular reflectance properties of indoor real static scenes. Using an RGB-D sensor, we further estimate the 3D position of light sources responsible for specular phenomena and propose a novel...
Automatic 2D-to-3D conversion aims to reduce the existing gap between the scarce 3D content and the incremental amount of displays that can reproduce this 3D content. Here, we present an automatic 2D-to-3D conversion algorithm that extends the functionality of the most of the existing machine learning based conversion approaches to deal with moving objects in the scene, and not only with static backgrounds...
A 3D motion detection method based on RGB-D data and scene flow clustering is proposed in this paper. The 3D extension of the optical flow called scene flow which describes the 3D motion of every point in a scene between two consecutive frames. Firstly, we estimate the scene flow using color maps and the aligned depth maps in two consecutive frames, then extract the feature vector of each point from...
While the problem of tracking 3D human motion has been widely studied, the top view is never taken into consideration. However, for the video surveillance, the camera is most of the time placed above the persons. This is due to the human shape is more discriminative in the front view. We propose in this paper a markerless 3D human tracking on the top view. To do this we use the depth and color image...
This paper presents a method to estimate a depth map using an infrared projector and a pair of infrared color cameras that can capture infrared and color images simultaneously. The infrared projector projects a dot pattern so that the cameras capture infrared images of a scene textured by the dots with which depths to surfaces in the scene can be estimated regardless of whether they have visible textures...
2D-to-3D conversion is an important task for reducing the current gap between the number of 3D displays and the available 3D content. Here, we present an automatic 2D-to-3D image conversion approach based on machine learning principles. Stemming from the hypothesis that images with a similar structure have likely a similar 3D structure, the depth of a query color image is estimated using a color plus...
Reliable surface normal computation is fundamental for a broad range of computer vision application areas, e.g. object segmentation, classification and recognition. Naturally, the surface normal is computed on the acquired depth data, whereby the normal quality is dependent on noise performance and resolution of the underlying image modality. The tendency of combining different imaging sensors into...
This paper introduces improvements to estimate 3D object pose from point clouds. We use point-pair feature for matching instead of traditional approaches using local feature descriptors. In order to obtain high accuracy estimation, a discriminative descriptor is introduced for point-pair features. The object model is a set of point pair descriptors computed from CAD model. The voting process is performed...
A novel method for predicting the ratings of video content on the basis of a viewer's behavior in a typical home environment is proposed. Using an input signal provided by a Kinect sensor, it identifies the presence of a viewer by extracting key point trajectories in video sequences of that viewer. It then estimates whether the viewer is gazing at the video content or not on the basis of the viewer's...
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