Sensor planning method for visual tracking in 3D camera networks

Most sensors or cameras discussed in the sensor network community are usually 3D homogeneous, even though their2 D coverage areas in the ground plane are heterogeneous. Meanwhile, observed objects of camera networks are usually simplified as 2D points in previous literature. However in actual application scenes, not only cameras are always heterogeneous with different height and action radiuses, but also the observed objects are with 3D features（i.e., height）. This paper presents a sensor planning formulation addressing the efficiency enhancement of visual tracking in 3D heterogeneous camera networks that track and detect people traversing a region. The problem of sensor planning consists of three issues：（i） how to model the 3D heterogeneous cameras;（ii） how to rank the visibility, which ensures that the object of interest is visible in a camera＇s field of view;（iii） how to reconfigure the 3D viewing orientations of the cameras. This paper studies the geometric properties of 3D heterogeneous camera networks and addresses an evaluation formulation to rank the visibility of observed objects. Then a sensor planning method is proposed to improve the efficiency of visual tracking. Finally, the numerical results show that the proposed method can improve the tracking performance of the system compared to the conventional strategies.

A Skeletal Camera Network for Close-range Images with a Data Driven Approach in Analyzing Stereo Configuration

Structure-from-Motion(SfM)techniques have been widely used for 3D geometry reconstruction from multi-view images.Nevertheless,the efficiency and quality of the reconstructed geometry depends on multiple factors,i.e.,the base-height ratio,intersection angle,overlap,and ground control points,etc.,which are rarely quantified in real-world applications.To answer this question,in this paper,we take a data-driven approach by analyzing hundreds of terrestrial stereo image configurations through a typical SfM algorithm.Two main meta-parameters with respect to base-height ratio and intersection angle are analyzed.Following the results,we propose a Skeletal Camera Network(SCN)and embed it into the SfM to lead to a novel SfM scheme called SCN-SfM,which limits tie-point matching to the remaining connected image pairs in SCN.The proposed method was applied in three terrestrial datasets.Experimental results have demonstrated the effectiveness of the proposed SCN-SfM to achieve 3D geometry with higher accuracy and fast time efficiency compared to the typical SfM method,whereas the completeness of the geometry is comparable.

Trifocal tensor based side information generation for multi-view distributed video code

Distributed video coding （DVC） is a new video coding approach based on Wyner-Ziv theorem. The novel uplink-friendly DVC, which offers low-complexity, low-power consuming, and low-cost video encoding, has aroused more and more research interests. In this paper a new method based on multiple view geometry is presented for spatial side information generation of uncalibrated video sensor network. Trifocal tensor encapsulates all the geometric relations among three views that are independent of scene structure; it can be computed from image correspondences alone without requiring knowledge of the motion or calibration. Simulation results show that trifocal tensor-based spatial side information improves the rate-distortion performance over motion compensation based interpolation side information by a maximum gap of around 2dB. Then fusion merges the different side information （temporal and spatial） in order to improve the quality of the final one. Simulation results show that the rate-distortion gains about 0.4 dB.

A displacement-relay videometric method for surface subsidence surveillance in unstable areas

When measuring the surface subsidence of unstable areas such as railroad beds and large construction fields, it is not practical to always find stable positions to install measurement instruments. Yet installing those instruments in unstable positions will cause measurement errors or even the complete failure of long-term subsidence surveillance. In this paper, the innovative concept and its method of "displacement-relay videometrics" are proposed. With the method, a double-headed camera is designed, and two constraints, the "fixation constraint" and the "homologous constraint", are established to construct the displacement-relay measurement equations, which can concurrently give the subsidence of the points to be measured and the positions where the cameras are fixed. The method and its measurement system are thus capable of automatically measuring the surface subsidence under the condition that the cameras are mounted on unstable locations over long durations. Therefore, the method has the broad prospect of undertaking automatic, long-term and continuous measurement for surface subsidence in engineering projects such as railroad beds, bridges and the ground beds of tall buildings. The proposed method opens a new area that cameras can be mounted on unstable platform to make high accuracy measurements, which is of great significance for applications.