Hybrid tree guided PatchMatch and quantizing acceleration for multiple views disparity estimation

Existing stereo matching methods cannot guarantee both the computational accuracy and efficiency for ihe disparity estimation of large-scale or multi-view images.Hybrid tree method can obtain a disparity estimation fast with relatively low accuracy,while PatchMatch can give high-precision disparity value with relatively high computational cost.In this work,we propose the Hybrid Tree Guided PatchMatch which can calculate the disparity fast and accurate.Firstly,an initial disparity map is estimated by employing hybrid tree cost aggregation,which is used to constrain the label searching range of the PatchMatch.Furthermore,a reliable normal searching range for each current normal vector defined on the initial disparity map is calculated to refine the PatchMatch.Finally,an effective quantizing acceleration strategy is designed to decrease the matching computational cost of continuous disparity.Experimental results demonstrate that the disparity estimation based on our algorithm is better in binocular image benchmarks such as Middlebury and KITTI.We also provide the disparity estimation results for multi-view stereo in real scenes.

Propagation-based incremental triangulation for multiple views 3D reconstruction

To balance the accuracy and efficiency in multiple-view triangulation with sequential images, a high-efficiency propagationbased incremental triangulation(INT) method, carving three-dimensional(3 D) scene points by updating the incoming feature track one by one without iterations, is proposed. Based on the INT method, a more accurate iteration-limited INT method is also established with few iterations to bound the propagated errors, ensuring the accuracy of subsequent3 D reconstruction. Finally, experimental results demonstrate that the proposed methods can balance the efficiency and accuracy in different multiple-view INT situations.

3-D Free-form Shape Measuring System Using Unconstrained Range Sensor

Three-dimensional（3-D） free-form shape measurement,a challenging task pursued by computer vision,is mainly characterized with single view acquisition and multiple view registration.Most of the conventional scanning systems are less flexibility and difficult to realize engineering applications for employing sequential registration tactic.To develop portable scanning system and engineering registration method overcoming problems of error accumulation and propagation is the research direction.In this paper,one 3-D free-form shape measuring system using unconstrained range sensor is designed.A quasi-active stereo binocular visual sensor embedded within a scanning mechanism is used as the range sensor.Error compensation is performed by residual amendment according to camera calibration lattice.Artificial control points are designed and adhered on object and one camera is introduced to shot these control points from different positions and orientations.Then ray bundle adjustment（BA） method is used to calculate the space coordinates of all the control points,so as to set up a global control net work.Registration can be completed by mapping at least 3 control points observed by range sensor in single view acquisition into the global control network.In this system,no calibration for laser plane is required and the motion of range sensor is completely free.The overlapping of neighboring region is unessential for registration.Therefore,the working range of the system can be easily extended.The measuring precision mainly depends on the quality of global control network.The sequential distances of coding control points are observed by electronic theodolites and then compared with those obtained according to BA result.Experimental results show that relative distance error of control points is no more than 0.2%.The proposed measuring system is portable,provides good capacity for global error control,and contributes to the engineering application of 3-D free-form shape measurement.

Multiview Visibility Estimation for Image-Based Modeling

In this paper, we investigate the problem of determining regions in 3D scene visible to some given viewpoints when obstacles are present in the scene. We assume that the obstacles are composed of some opaque objects with closed surfaces. The problem is formulated in an implicit framework where the obstacles are represented by a level set function. The visible and invisible regions of the given viewpoints are determined through an efficient implicit ray tracing technique. As an extension of our approach, we apply the multiview visibility estimation to an image-based modeling technique. The unknown scene geometry and multiview visibility information are incorporated into a variational energy functional. By minimizing the energy functional, the true scene geometry as well as the accurate visibility information of the multiple views can be recovered from a number of scene images. This makes it feasible to handle the visibility problem of multiple views by our approach when the true scene geometry is unknown.