From Multiview Image Curves to 3D Drawings

Reconstructing 3D scenes from multiple views has made impressive strides in recent years, chiefly by correlating isolated feature points, intensity patterns, or curvilinear structures. In the general setting - without controlled acquisition, abundant texture, curves and surfaces following specific models or limiting scene complexity - most methods produce unorganized point clouds, meshes, or voxel representations, with some exceptions producing unorganized clouds of 3D curve fragments. Ideally, many applications require structured representations of curves, surfaces and their spatial relationships. This paper presents a step in this direction by formulating an approach that combines 2D image curves into a collection of 3D curves, with topological connectivity between them represented as a 3D graph. This results in a 3D drawing, which is complementary to surface representations in the same sense as a 3D scaffold complements a tent taut over it. We evaluate our results against truth on synthetic and real datasets.Comment: Expanded ECCV 2016 version with tweaked figures and including an overview of the supplementary material available at multiview-3d-drawing.sourceforge.ne

Study of optical techniques for the Ames unitary wind tunnels. Part 4: Model deformation

A survey of systems capable of model deformation measurements was conducted. The survey included stereo-cameras, scanners, and digitizers. Moire, holographic, and heterodyne interferometry techniques were also looked at. Stereo-cameras with passive or active targets are currently being deployed for model deformation measurements at NASA Ames and LaRC, Boeing, and ONERA. Scanners and digitizers are widely used in robotics, motion analysis, medicine, etc., and some of the scanner and digitizers can meet the model deformation requirements. Commercial stereo-cameras, scanners, and digitizers are being improved in accuracy, reliability, and ease of operation. A number of new systems are coming onto the market

Online Mutual Foreground Segmentation for Multispectral Stereo Videos

The segmentation of video sequences into foreground and background regions is a low-level process commonly used in video content analysis and smart surveillance applications. Using a multispectral camera setup can improve this process by providing more diverse data to help identify objects despite adverse imaging conditions. The registration of several data sources is however not trivial if the appearance of objects produced by each sensor differs substantially. This problem is further complicated when parallax effects cannot be ignored when using close-range stereo pairs. In this work, we present a new method to simultaneously tackle multispectral segmentation and stereo registration. Using an iterative procedure, we estimate the labeling result for one problem using the provisional result of the other. Our approach is based on the alternating minimization of two energy functions that are linked through the use of dynamic priors. We rely on the integration of shape and appearance cues to find proper multispectral correspondences, and to properly segment objects in low contrast regions. We also formulate our model as a frame processing pipeline using higher order terms to improve the temporal coherence of our results. Our method is evaluated under different configurations on multiple multispectral datasets, and our implementation is available online.Comment: Preprint accepted for publication in IJCV (December 2018

Depth map compression via 3D region-based representation

In 3D video, view synthesis is used to create new virtual views between encoded camera views. Errors in the coding of the depth maps introduce geometry inconsistencies in synthesized views. In this paper, a new 3D plane representation of the scene is presented which improves the performance of current standard video codecs in the view synthesis domain. Two image segmentation algorithms are proposed for generating a color and depth segmentation. Using both partitions, depth maps are segmented into regions without sharp discontinuities without having to explicitly signal all depth edges. The resulting regions are represented using a planar model in the 3D world scene. This 3D representation allows an efficient encoding while preserving the 3D characteristics of the scene. The 3D planes open up the possibility to code multiview images with a unique representation.Postprint (author's final draft

LEVEL-BASED CORRESPONDENCE APPROACH TO COMPUTATIONAL STEREO

One fundamental problem in computational stereo reconstruction is correspondence. Correspondence is the method of detecting the real world object reflections in two camera views. This research focuses on correspondence, proposing an algorithm to improve such detection for low quality cameras (webcams) while trying to achieve real-time image processing. Correspondence plays an important role in computational stereo reconstruction and it has a vast spectrum of applicability. This method is useful in other areas such as structure from motion reconstruction, object detection, tracking in robot vision and virtual reality. Due to its importance, a correspondence method needs to be accurate enough to meet the requirement of such fields but it should be less costly and easy to use and configure, to be accessible by everyone. By comparing current local correspondence method and discussing their weakness and strength, this research tries to enhance an algorithm to improve previous works to achieve fast detection, less costly and acceptable accuracy to meet the requirement of reconstruction. In this research, the correspondence is divided into four stages. Two stages of preprocessing which are noise reduction and edge detection have been compared with respect to different methods available. In the next stage, the feature detection process is introduced and discussed focusing on possible solutions to reduce errors created by system or problem occurring in the scene such as occlusion. Lastly, in the final stage it elaborates different methods of displaying reconstructed result. Different sets of data are processed based on the steps involved in correspondence and the results are discussed and compared in detail. The finding shows how this system can achieve high speed and acceptable outcome despite of poor quality input. As a conclusion, some possible improvements are proposed based on ultimate outcome

3D Reconstruction through Segmentation of Multi-View Image Sequences

We propose what we believe is a new approach to 3D reconstruction through the design of a 3D voxel volume, such that all the image information and camera geometry are embedded into one feature space. By customising the volume to be suitable for segmentation, the key idea that we propose is the recovery of a 3D scene through the use of globally optimal geodesic active contours. We also present an extension to this idea by proposing the novel design of a 4D voxel volume to analyse the stereo motion problem in multi-view image sequences