3DV quality model based depth maps for view synthesis in FTV system

Depth maps are used for synthesis virtual view in free-viewpoint television （FTV） systems. When depth maps are derived using existing depth estimation methods, the depth distortions will cause undesirable artifacts in the synthesized views. To solve this problem, a 3D video quality model base depth maps （D-3DV） for virtual view synthesis and depth map coding in the FTV applications is proposed. First, the relationships between distortions in coded depth map and rendered view are derived. Then, a precisely 3DV quality model based depth characteristics is develop for the synthesized virtual views. Finally, based on D-3DV model, a multilateral filtering is applied as a pre-processed filter to reduce rendering artifacts. The experimental results evaluated by objective and subjective methods indicate that the proposed D-3DV model can reduce bit-rate of depth coding and achieve better rendering quality.

Prestack Depth Migration by a Parallel 3D PSPI

Prestack depth migration for seismic reflection data is commonly used tool for imaging complex geological structures such as salt domes, faults, thrust belts, and stratigraphic structures. Phase shift plus interpolation (PSPI) algorithm is a useful tool to directly solve a wave equation and the results have natural properties of the wave equation. Amplitude and phase characteristics, in particular, are better preserved. The PSPI algorithm is widely used in hydrocarbon exploration because of its simplicity, efficiency, and reduced efforts for computation. However, meaningful depth image of 3D subsurface requires parallel computing to handle heavy computing time and great amount of input data. We implemented a parallelized version of 3D PSPI for prestack depth migration using Open-Multi-Processing (Open MP) library. We verified its performance through applications to 3D SEG/EAGE salt model with a small scale Linux cluster. Phase-shift was performed in the vertical and horizontal directions, respectively, and then interpolated at each node. This gave a single image gather according to shot gather. After summation of each single image gather, we got a 3D stacked image in the depth domain. The numerical model example shows good agree- ment with the original geological model.

Using structure restoration maps to comprehensively identify potential faults and fractures in compressional structures

Faults and fractures of multiple scales are frequently induced and generated in compressional structural system. Comprehensive identification of these potential faults and fractures that cannot be distinguished directly from seismic profile of the complex structures is still an unanswered problem. Based on the compressional structural geometry and kinematics theories as well as the structural interpretation from seismic data, a set of techniques is established for the identification of potential faults and fractures in compressional structures. Firstly, three-dimensional(3D) patterns and characteristics of the faults directly interpreted from seismic profile were illustrated by 3D structural model. Then, the unfolding index maps, the principal structural curvature maps, and tectonic stress field maps were obtained from structural restoration. Moreover, potential faults and fractures in compressional structures were quantitatively identified relying on comprehensive analysis of these three maps. Successful identification of the potential faults and fractures in Mishrif limestone formation and in Asmari dolomite formation of Buzurgan anticline in Iraq demonstrates the applicability and reliability of these techniques.

Co-axial depth sensor with an extended depth range for AR/VR applications

Background Depth sensor is an essential element in virtual and augmented reality devices to digitalize users'environment in real time.The current popular technologies include the stereo,structured light,and Time-of-Flight(ToF).The stereo and structured light method require a baseline separation between multiple sensors for depth sensing,and both suffer from a limited measurement range.The ToF depth sensors have the largest depth range but the lowest depth map resolution.To overcome these problems,we propose a co-axial depth map sensor which is potentially more compact and cost-effective than conventional structured light depth cameras.Meanwhile,it can extend the depth range while maintaining a high depth map resolution.Also,it provides a high-resolution 2 D image along with the 3 D depth map.Methods This depth sensor is constructed with a projection path and an imaging path.Those two paths are combined by a beamsplitter for a co-axial design.In the projection path,a cylindrical lens is inserted to add extra power in one direction which creates an astigmatic pattern.For depth measurement,the astigmatic pattern is projected onto the test scene,and then the depth information can be calculated from the contrast change of the reflected pattern image in two orthogonal directions.To extend the depth measurement range,we use an electronically focus tunable lens at the system stop and tune the power to implement an extended depth range without compromising depth resolution.Results In the depth measurement simulation,we project a resolution target onto a white screen which is moving along the optical axis and then tune the focus tunable lens power for three depth measurement subranges,namely,near,middle and far.In each sub-range,as the test screen moves away from the depth sensor,the horizontal contrast keeps increasing while the vertical contrast keeps decreasing in the reflected image.Therefore,the depth information can be obtained by computing the contrast ratio between features in orthogonal directions.Conclusions The proposed depth map sensor could implement depth measurement for an extended depth range with a co-axial design.

Edge-Preserving Depth Map Super-Resolution with Intensity Guidance

Depth discontinuity edge affects the visual quality of synthesized images in 3D image warping.However,it suffers from accuracy degradation when up-sampled from low-resolution depth maps,especially at large scaling factors.To preserve the accuracy of depth discontinuity,a novel joint bilateral depth super-resolution with intensity guidance method is proposed.Particularly,the fast local intensity classification is exploited to estimate depth coefficients in joint bilateral up-sampling for depth maps,so as to eliminate depth discontinuity edge misalignment.Additionally,the proposed method is accelerated on graphic processing units(GPUs)to meet the requirement of realtime application.Experiments demonstrate that our method can preserve the accuracy of depth discontinuity edges after super resolution,leveraging the visual quality of synthesized image in 3D image warping.

ArthroNet:a monocular depth estimation technique with 3D segmented maps for knee arthroscopy

Background Lack of depth perception from medical imaging systems is one of the long-standing technological limitations of minimally invasive surgeries.The ability to visualize anatomical structures in 3D can improve conventional arthroscopic surgeries,as a full 3D semantic representation of the surgical site can directly improve surgeons’ability.It also brings the possibility of intraoperative image registration with preoperative clinical records for the development of semi-autonomous,and fully autonomous platforms.This study aimed to present a novel monocular depth prediction model to infer depth maps from a single-color arthroscopic video frame.Methods We applied a novel technique that provides the ability to combine both supervised and self-supervised loss terms and thus eliminate the drawback of each technique.It enabled the estimation of edge-preserving depth maps from a single untextured arthroscopic frame.The proposed image acquisition technique projected artificial textures on the surface to improve the quality of disparity maps from stereo images.Moreover,following the integration of the attention-ware multi-scale feature extraction technique along with scene global contextual constraints and multiscale depth fusion,the model could predict reliable and accurate tissue depth of the surgical sites that complies with scene geometry.Results A total of 4,128 stereo frames from a knee phantom were used to train a network,and during the pre-trained stage,the network learned disparity maps from the stereo images.The fine-tuned training phase uses 12,695 knee arthroscopic stereo frames from cadaver experiments along with their corresponding coarse disparity maps obtained from the stereo matching technique.In a supervised fashion,the network learns the left image to the disparity map transformation process,whereas the self-supervised loss term refines the coarse depth map by minimizing reprojection,gradients,and structural dissimilarity loss.Together,our method produces high-quality 3D maps with minimum re-projection loss that are 0.0004132(structural similarity index),0.00036120156(L1 error distance)and 6.591908×10^(−5)(L1 gradient error distance).Conclusion Machine learning techniques for monocular depth prediction is studied to infer accurate depth maps from a single-color arthroscopic video frame.Moreover,the study integrates segmentation model hence,3D segmented maps are inferred that provides extended perception ability and tissue awareness.

3D printing of conch-like scaffolds for guiding cell migration and directional bone growth

Regeneration of severe bone defects remains an enormous challenge in clinic.Developing regenerative scaffolds to directionally guide bone growth is a potential strategy to overcome this hurdle.Conch,an interesting creature widely spreading in ocean,has tough spiral shell that can continuously grow along the spiral direction.Herein,inspired by the physiological features of conches,a conch-like(CL)scaffold based onβ-TCP bioceramic material was successfully prepared for guiding directional bone growth via digital light processing(DLP)-based 3D printing.Benefiting from the spiral structure,the CL scaffolds significantly improved cell adhesion,proliferation and osteogenic differentiation in vitro compared to the conventional 3D scaffolds.Particularly,the spiral structure in the scaffolds could efficiently induce cells to migrate from the bottom to the top of the scaffolds,which was like“cells climbing stairs”.Furthermore,the capability of guiding directional bone growth for the CL scaffolds was demonstrated by a special half-embedded femoral defects model in rabbits.The new bone tissue could consecutively grow into the protruded part of the scaffolds along the spiral cavities.This work provides a promising strategy to construct biomimetic biomaterials for guiding directional bone tissue growth,which offers a new treatment concept for severe bone defects,and even limb regeneration.

Vision Based Hand Gesture Recognition Using 3D Shape Context

Hand gesture recognition is a popular topic in computer vision and makes human-computer interaction more flexible and convenient.The representation of hand gestures is critical for recognition.In this paper,we propose a new method to measure the similarity between hand gestures and exploit it for hand gesture recognition.The depth maps of hand gestures captured via the Kinect sensors are used in our method,where the 3D hand shapes can be segmented from the cluttered backgrounds.To extract the pattern of salient 3D shape features,we propose a new descriptor-3D Shape Context,for 3D hand gesture representation.The 3D Shape Context information of each 3D point is obtained in multiple scales because both local shape context and global shape distribution are necessary for recognition.The description of all the 3D points constructs the hand gesture representation,and hand gesture recognition is explored via dynamic time warping algorithm.Extensive experiments are conducted on multiple benchmark datasets.The experimental results verify that the proposed method is robust to noise,articulated variations,and rigid transformations.Our method outperforms state-of-the-art methods in the comparisons of accuracy and efficiency.

2D/3D工区构造成图技术流程探讨

文章探讨了 2D/3D工区的构造成图技术流程 ,指出了构造成图传统方法中影响成图精度的主要因素 ,从解决问题入手 ,提出了相应的平均速度体建立及构造成图流程。对二维工区 ,采用了“似变速空校”方法 ,并通过编制空校量板 ,实现了二维偏移剖面的交点闭合和测点的三维空间偏移归位 ,提高了成图精度。而对三维工区 ,则应用了LM的时深转换一体化模块 ,借助三维可视化技术 ,结合多种地震地质信息 ,对平均速度体进行交互式修正。实际应用表明 ,该流程提高了构造成图的精度和工作效率 ,是一套省时实用的构造成图技术流程。

Depth map resolution improvement for 3D range-intensity correlation laser imaging

This Letter proposes a high bit-depth coding method to improve depth map resolution and render it suitable to human-eye observation in 3D range-intensity correlation laser imaging. In this method, a high bit-depth CCD camera with a nanosecond-sealed gated intensifier is used as an image sensor; subsequently two high bit-depth gate images with specific range-intensity profiles are obtained to establish the gray depth map and finally the gray depth map is encoded by an equidensity pseudocolor. With this method, a color depth map is generated with higher range resolution. In our experimental work, the range resolution of the depth map is improved by a factor of 1.67.

SIRIUS3D叠前深度偏移软件在BZ25—1构造上的应用

介绍了SIRIUS3D叠前深度偏移软件的技术特点及工作流程,分析了该软件的优点和不足.将该软件首次应用于BZ25-1构造,通过精细的速度反演,建立了较为准确的三维速度模型,最终叠前深度偏移结果较为理想,尤其是中浅层复杂断层的成像质量得到明显提高,为BZ25-1构造评价提供了重要依据.

基于动态语义特征的视觉SLAM系统

针对视觉SLAM(Simultaneous Localization and Mapping)在真实场景下出现动态物体(如行人,车辆、动物)等影响算法定位和建图精确性的问题,基于ORB-SLAM3(Oriented FAST and Rotated BRIEF-Simultaneous Localization and Mapping 3)提出了YOLOv3-ORB-SLAM3算法。该算法在ORB-SLAM3的基础上增加了语义线程,采用动态和静态场景特征提取双线程机制:语义线程使用YOLOv3对场景中动态物体进行语义识别目标检测,同时对提取的动态区域特征点进行离群点剔除;跟踪线程通过ORB特征提取场景区域特征,结合语义信息获得静态场景特征送入后端,从而消除动态场景对系统的干扰,提升视觉SLAM算法定位精度。利用TUM(Technical University of Munich)数据集验证,结果表明YOLOv3-ORB-SLAM3算法在单目模式下动态序列相比ORB-SLAM3算法ATE(Average Treatment Effect)指标下降30%左右,RGB-D(Red,Green and Blue-Depth)模式下动态序列ATE指标下降10%,静态序列未有明显下降。

Sparse RGB-D images create a real thing:A flexible voxel based 3D reconstruction pipeline for single object

Reconstructing 3D models for single objects with complex backgrounds has wide applications like 3D printing,AR/VR,and so on.It is necessary to consider the tradeoff between capturing data at low cost and getting high-quality reconstruction results.In this work,we propose a voxel-based modeling pipeline with sparse RGB-D images to effectively and efficiently reconstruct a single real object without the geometrical post-processing operation on background removal.First,referring to the idea of VisualHull,useless and inconsistent voxels of a targeted object are clipped.It helps focus on the target object and rectify the voxel projection information.Second,a modified TSDF calculation and voxel filling operations are proposed to alleviate the problem of depth missing in the depth images.They can improve TSDF value completeness for voxels on the surface of the object.After the mesh is generated by the MarchingCube,texture mapping is optimized with view selection,color optimization,and camera parameters fine-tuning.Experiments on Kinect capturing dataset,TUM public dataset,and virtual environment dataset validate the effectiveness and flexibility of our proposed pipeline.

Accuracy and utility of the Structure Sensor for collecting 3D indoor information

This paper presents the result of an investigation into the utility of the Structure Sensor developed by Occipital Inc.and accuracy of its output for 3D surveying of interiors of buildings in relation to Surveying(Cadastral Survey)Regulation 2005 in Victoria,Australia.The paper investigates data acquisition issues,defines guidelines to obtain the best reconstruction result,and evaluates the result against the requirements set by the Regulation.The findings suggest a mixed result.The sensor delivers more accurate outputs for the smaller room sizes.Also,the accuracy does not meet the requirements,but it was found to be close to what is expected in the Regulation.Finally,the paper argues that the device is user-friendly enough to be used by non-experts for crowdsourcing indoor information and,the accuracy of its output can meet the needs of other domains such as indoor navigation and public safety.

3D HYBRID DEPTH MIGRATION AND FOUR-WAY SPLITTING SCHEMES

The alternately directional implicit （ADI） scheme is usually used in 3D depth migration. It splits the 3D square-root operator along crossline and inline directions alternately. In this paper, based on the ideal of data line, the four-way splitting schemes and their splitting errors for the finite-difference （FD） method and the hybrid method are investigated. The wavefield extrapolation of four-way splitting scheme is accomplished on a data line and is stable unconditionally. Numerical analysis of splitting errors show that the two-way FD migration have visible numerical anisotropic errors, and that four-way FD migration has much less splitting errors than two-way FD migration has. For the hybrid method, the differences of numerical anisotropic errors between two-way scheme and four-way scheme are small in the case of lower lateral velocity variations. The schemes presented in this paper can be used in 3D post-stack or prestack depth migration. Two numerical calculations of 3D depth migration are completed. One is the four-way FD and hybrid 3D post-stack depth migration for an impulse response, which shows that the anisotropic errors can be eliminated effectively in the cases of constant and variable velocity variations. The other is the 3D shot-profile prestack depth migration for SEG/EAEG benchmark model with two-way hybrid splitting scheme, which presents good imaging results. The Message Passing Interface （MPI） programme based on shot number is adopted.

Methods for wave equation prestack depth migration and numerical experiments

In this paper the methods of wave theory based prestack depth migration and their implementation are studied. Using the splitting of wave operator, the wavefield extrapolation equations are deduced and the numerical schemes are presented. The numerical tests for SEG/EAEG model with MPI are performed on the PC-cluster. The numerical results show that the methods of single-shot (common-shot) migration and synthesized-shot migration are of practical values and can be applied to field data processing of 3D prestack depth migration.

地震速度场建立与变速构造成图的一种方法

马海珍 ,雍学善 ,杨午阳 ,鲁烈琴 ,王小卫 .地震速度场建立与变速构造成图的一种方法 .石油地球物理勘探 ,2 0 0 2 ,37(1) :5 3～ 5 9本文剖析了地震速度场建立与变速构造成图传统方法中影响成图精度的主要因素 ,指出了传统方法中造成误差较大、准确性较低的原因。从解决传统方法中存在的问题入手 ,提出了相应的速度场建立与变速构造成图方法 ,指出了在浮动基准面地震工区中使用本方法的条件和要求 ,并将其扩展为适合于深度偏移的层速度建模方法。本方法采用层位反偏移技术、沿层横向叠加速度谱剖面技术、三维空间射线追踪层速度相干反演技术和图形偏移构造成图技术 ,对各反射目的层位进行单层速度场建立与构造成图 ,解决了传统方法中影响速度场和构造图精度的主要问题。实际应用表明 ,该方法提高了速度场建立与构造成图的精度 ,是一套技术先进。

基于反射层的变层速度模型时深转换方法

基于反射波法的地震勘探技术是在时间域中认识地下地质情况的 ,由于地震波传播速度场的变化 ,反射成像和地下地质体间并非是一个简单的镜像对称关系 ,而是一种变异的镜像结果。要正确的认识地下地质体 ,必须把时间域中的地震数据恢复到深度域中。在断裂发育的断块区或复杂的逆掩构造区 ,由于断层错动及地层褶皱等因素 ,具有不同速度特征的地层在断层处相互接触或同一套地层多次重复。在这些地方地下空间速度场在短距离内会产生很大的变化 ,速度场变得相当复杂 ,准确的时深转换成为一件非常困难的事情。文章以反射层、断层面等时间域中的地质边界为约束条件 ,以钻井资料建立基础速度结构 ,采用“基于反射层的变层速度模型结构建立时深转换速度场”方法 ,实现精确时深转换。该方法应用灵活、建场方式直观 。

二维叠前深度偏移连片处理及成像建模技术

塔里木盆地塔中地区深层低幅度构造是有利的含油气区 ,但因构造探明程度低 ,很难准确确定钻探井位 ,再加上一些地区利用二维地震资料做构造图 ,使得小幅度构造的可靠性进一步降低。为了在利用二维地震资料条件下提高深层小幅度构造的可靠性 ,进一步提高构造成像的真实性 ,提出了如下研究思路 :在时间域解决近地表静校正闭合差和提高资料信噪比 ;在深度域消除相交测线的速度闭合差 ;进行二维叠前深度偏移连片处理。基于这种思路 ,在时间域首先对每条二维测线做初至折射静校正 ,以便消除由近地表引起的剖面闭合差。然后利用二维测线按照三维叠前深度偏移方法建立全区统一的速度场 ,并从该速度场中抽取每条二维测线的叠前深度偏移速度场 ,使每条二维测线准确成像。从最终结果来看 ,新剖面较老剖面在信噪比和成像精度上有较大的提高 ,新落实的小幅度构造与井分层数据吻合较好。因此认为 ,依据所提思路和方法进行连片处理较好地解决了中深层低幅度构造的成像问题。

三维多值走时地震波场重建及格林函数计算

针对三维复杂介质地震波传播数值计算中出现的多值走时情况，阐述了地震波场重建及格林函数计算中的困难，提出一种在相空间拉格朗日流形上的波场重建及格林函数计算方法．本文算法应用于三维叠前深度偏移处理流程时，可高效地获得均匀网格点上地震波多值走时及振幅的数值计算结果．文中还阐明两类数值计算过程判据，以在多值走时区域及计算的全区域中，控制射线追踪过程中的射线密度及格林函数计算精度．算例验证了本文方法的有效性．