Quadcopter localization and health monitoring method based on multiple virtual silhouette sensor integration

With the widespread deployment of quadcopters, the flight safety issue attracts increasingly public and academic attentions. This article presents a quadcopter flight regime extraction algorithm for quadcopter localization and health monitoring using imageries captured by general purpose monocular cameras. First, contour information is extracted from quadcopter shadows on the ground. In order to better illustrate the three-dimensional silhouette information contained in shadow contour on the ground, a virtual sensor named Shadow Projection Tunnel is designed. Then, multiple Shadow Projection Tunnels are generated according to the extracted silhouette information and corresponding light source positions. Finally, three-dimensional quadcopter positions and flight regimes are extracted based on the aggregation between multiple Shadow Projection Tunnels. The proposed method is validated to be accurate and efficient in monitoring quadcopter position and flight regimes based on the comparative analyses. In comparison with traditional quadcopter health monitoring methods, the proposed method has advantages on deployment convenience, system robustness, precision expandability, and scenario adaptability, making it an ideal solution for quadcopter monitoring in outdoor scenarios.

Fusing Depth and Silhouette for Scanning Transparent Object with RGB-D Sensor

3D reconstruction based on structured light or laser scan has been widely used in industrial measurement, robot navigation, and virtual reality. However, most modern range sensors fail to scan transparent objects and some other special materials, of which the surface cannot reflect back the accurate depth because of the absorption and refraction of light. In this paper, we fuse the depth and silhouette information from an RGB-D sensor (Kinect v1) to recover the lost surface of transparent objects. Our system is divided into two parts. First, we utilize the zero and wrong depth led by transparent materials from multiple views to search for the 3D region which contains the transparent object. Then, based on shape from silhouette technology, we recover the 3D model by visual hull within these noisy regions. Joint Grabcut segmentation is operated on multiple color images to extract the silhouette. The initial constraint for Grabcut is automatically determined. Experiments validate that our approach can improve the 3D model of transparent object in real-world scene. Our system is time-saving, robust, and without any interactive operation throughout the process.

Human Motion Analysis Based On Silhouette and Centroid Displacement

Human motion analysis in an intelligence surveillance system is a hot research topic in computer vision field.In this paper we proposed a motion recognition method based on silhouette information and centroid displacement for static environment.We used background subtraction method added background update and did binarization processing on foreground image by using adaptive threshold segmentation technique,then extracted moving target from the videos.Last we used silhouette information and centroid displacement as human motion features for behaviour analysis.Experiments show that the method has high accuracy rate at daily behaviour recognition.

Soccer Player’s Pose Recognition by Creative Search for Generating Free Viewpoint Images

The low-cost generation we have proposed for a free viewpoint image of soccer games uses a multiple viewpoint image database designed with computer graphics for recognizing player poses in the real image and for generating virtual scenes. A pose is recognized from a player’s silhouette and applying parametric eigenspace method. Because only silhouette information is used, however, limb positioning may be backward or the body misdirected. Our new proposal for excluding misplaced left and right limb poses assumes that changes in a pose, especially limb positioning, between sequential frames are continuous, so the limb positioning in 3D space and 2D images can be determined and the search range restricted in eigenspace. We also propose generating continuous frames for cases in which a correct pose exists outside of the restricted range by setting an initial state and handling error.