Research On Depth Image Estimation Algorithm Based On Camera Array

With the development of information science and computer technology, three-dimensional information acquisition has become the key technology in the areas of Industrial inspection, bio-medicine, virtual reality, etc, and three-dimensional information acquisition technology has a wide application prospect in machining, film special effects production, advanced gaming, conservation, costume design, three-dimensional communication, aerospace remote sensing, military reconnaissance, and so on. In these fields, people's requirements on three-dimensional information acquisition technology are increasingly high. Three-dimensional information acquisition technologies currently used, such as Multi-head stereo vision technology, Structured light technique, DFM or SFM(depth from motion or struction from motion),DFF and TOF(Time of flight), have their own advantages and disadvantages, and no single technology can satisfy requirements of real-time, high accuracy, high resolution and low cost. TOF technology is developed rapidly in recent years, its advantages are high accuracy, real-time, and low-cost, the disadvantage is that long distance will cause large uncertainty in the depth data, and spatial resolution is still relatively low. Multi-Stereo vision has been deeply studied and widely used. Its main drawbacks are large amount of stereo matching calculations; easily lead to false matches; and for the camera array system, its implementation cost is very expensive.This paper mainly studies on the depth map estimation algorithms based on camera array. Camera array used in this paper consists of one TOF camera and several visual cameras. Algorithms proposed in this paper seeks to generate high resolution depth image under the view of each visual camera, in this process only each visual itself and TOF camera are used. Passive stereo is not used in our methods.Firstly, a new calibration method between visual camera and Time-of-Flight camera is proposed, in which the intensity image and depth image of TOF camera are both used. In the experimental result, we can find that our new method works better than the traditional calibration method when it is used in the calibration between TOF camera and visual camera. Then, for different applications, a number of depth map estimation algorithms based on camera array are proposed in this paper. First, for indoor simple scene, we proposed a real-time depth map estimation algorithm for visual camera. The optimal depth value is calculated by minimizing the squared error. Second, a new depth map estimation algorithms based on camera array for the indoor complex scene is proposed. In this algorithm, the new energy function fuses two different kinds of data: the depth data and the color data, and makes sure that the proper data are always chosen when we are estimating the depth data of the pixels in the refinement procedure. Third, the depth map estimation algorithm in application of indoor complex scene is improved by introducing the uncertainty of TOF depth value and calibration parameters, and adopting the adaptive neighborhood calculating method. Experimental results of all algorithms show that the high resolution depth maps under the view of visual cameras are successfully generated and of high qualityFinally, we give the summary of the algorithms in this paper and the future researchdirections.