Rectified Surface Mosaics

We approach mosaicing as a camera tracking problem within a known parameterized surface. From a video of a camera moving within a surface, we compute a mosaic representing the texture of that surface, flattened onto a planar image. Our approach works by defining a warp between images as a function of surface geometry and camera pose. Globally optimizing this warp to maximize alignment across all frames determines the camera trajectory, and the corresponding flattened mosaic image. In contrast to previous mosaicing methods which assume planar or distant scenes, or controlled camera motion, our approach enables mosaicing in cases where the camera moves unpredictably through proximal surfaces, such as in medical endoscopy applications.     

多平面多视点单应矩阵间的约束

用代数方法系统地讨论了多平面多视点下单应矩阵间的约束关系.主要结论有(A)如 果视点间摄像机的运动为纯平移运动,则1)对于所有平面关于两视点间的单应矩阵的集合,或 单个平面关于所有视点的单应矩阵的集合的秩均等于4,2)对于多平面多视点的标准单应矩阵 的集合其秩仍等于4,3)根据以上结论可推出现有文献中关于"相对单应矩阵"约束的所有结 果;(B)如果视点间摄像机的运动为一般运动,则1)对于所有平面关于两个视点间的单应矩阵 集合的秩等于4的结论仍成立,2)对于其它情况其秩不再等于4而是等于9.     

Manifold Modeling and Its Application to Tubular Scene Manifold Mosaicing Algorithm

Manifold mosaicing is arguably the most important class of image mosaicing methods. The existing manifold mosaicing methods work reasonably well only for scenes with simple plane structure and for images taken in a usual way such that the camera??s motion direction is perpendicular to its optical axis. A novel manifold modeling theoretical framework is presented to unify the current image mosaicing methods. Based on this framework, an effective mosaicing algorithm is also proposed to mosaic tubular scenes which have failed most existing methods. We adopt a two-step shaping strategy to parallelize the optical flows and change the topological genus of the image strips by M?bius mappings and circular ring extending. We performed computational experiments via image sequences acquired from tubular scenes and obtained excellent panoramas. The theoretical framework and algorithms in this paper have immediate applications to many practical tubular scene mosaicing problems in medical imaging, industrial inspection, gaming, virtual reality and robotics.     

Minimal Aspect Distortion (MAD) Mosaicing of Long Scenes

Long scenes can be imaged by mosaicing multiple images from cameras scanning the scene. We address the case of a video camera scanning a scene while moving in a long path, e.g. scanning a city street from a driving car, or scanning a terrain from a low flying aircraft. A robust approach to this task is presented, which is applied successfully to sequences having thousands of frames even when using a hand-held camera. Examples are given on a few challenging sequences. The proposed system consists of two components: (i) Motion and depth computation. (ii) Mosaic rendering. In the first part a “direct” method is presented for computing motion and dense depth. Robustness of motion computation has been increased by limiting the motion model for the scanning camera. An iterative graph-cuts approach, with planar labels and a flexible similarity measure, allows the computation of a dense depth for the entire sequence. In the second part a new minimal aspect distortion (MAD) mosaicing uses depth to minimize the geometrical distortions of long panoramic images. In addition to MAD mosaicing, interactive visualization using X-Slits is also demonstrated. This research was supported by the Israel Science Foundation. Video examples and high resolution images can be viewed in .     

A generic structure-from-motion framework

We introduce a generic structure-from-motion approach based on a previously introduced, highly general imaging model, where cameras are modeled as possibly unconstrained sets of projection rays. This allows to describe most existing camera types including pinhole cameras, sensors with radial or more general distortions, catadioptric cameras (central or non-central), etc. We introduce a structure-from-motion approach for this general imaging model, that allows to reconstruct scenes from calibrated images, possibly taken by cameras of different types (cross-camera scenarios). Structure-from-motion is naturally handled via camera independent ray intersection problems, solved via linear or simple polynomial equations. We also propose two approaches for obtaining optimal solutions using bundle adjustment, where camera motion, calibration and 3D point coordinates are refined simultaneously. The proposed methods are evaluated via experiments on two cross-camera scenarios—a pinhole used together with an omni-directional camera and a stereo system used with an omni-directional camera.     

基于复值小波分解的图象拼合

图象拼合是一种基于图象的场景编码方法，它被很多基于图象的绘制IBR（image based rendering）系统采用，用来建立复杂的虚拟场景表示（例如，360°球面和柱面全景图、环境映照及高分辨率图象等）.基于复值小波多分辨率分解(Complex Wavelet Multiresolution Decomposition)提出了一种有效的图象拼合方法，它能同时地、逐步求精地对图象进行匹配和整合.首先，采用复值小波变换不仅可以保证全局优化的结果，还能够满足图象整合的规模不变和平移不变性.其次，基于多分辨     

Graph based construction of textured large field of view mosaics for bladder cancer diagnosis

Large field-of-view panoramic images greatly facilitate bladder cancer diagnosis and follow-up. Such 2D mosaics can be obtained by registering the images of a video-sequence acquired during cystoscopic examinations. The scientific challenge in the registration process lies in the strong inter- and intra-patient texture variability of the images, from which primitives cannot be robustly extracted. State-of-the-art registration methods are not at the same time robust and accurate, especially for image pairs with a small amount of overlap (less than 90%) or strong perspective transformations. Moreover, no previous contribution to cystoscopy mosaicing presents panoramic images created from multiple overlapping sequences (e.g. “zigzags” or loop trajectories). We show how such overlapping sections can be automatically detected and present a novel registration algorithm that robustly superimposes non-consecutive image pairs, which are related by stronger perspective transformations and share less overlap than consecutive images (less than 50%). Globally coherent panoramic images are constructed using a non-linear optimization and a novel contrast-enhancing stitching method. Results on both phantom and patient data are obtained using constant algorithm parameters, which demonstrate the robustness of the proposed method. While the methods presented in this contribution are specifically designed for cystoscopy mosaicing, they can also be applied to more general mosaicing problems. We demonstrate this on a traditional stitching application, where a set of pictures of a building are stitched into a seamless, globally coherent panoramic image.     

Online underwater optical mapping for trajectories with gaps

This paper proposes a vision-only online mosaicing method for underwater surveys. Our method tackles a common problem in low-cost imaging platforms, where complementary navigation sensors produce imprecise or even missing measurements. Under these circumstances, the success of the optical mapping depends on the continuity of the acquired video stream. However, this continuity cannot be always guaranteed due to the motion blurs or lack of texture, common in underwater scenarios. Such temporal gaps hinder the extraction of reliable motion estimates from visual odometry, and compromise the ability to infer the presence of loops for producing an adequate optical map. Unlike traditional underwater mosaicing methods, our proposal can handle camera trajectories with gaps between time-consecutive images. This is achieved by constructing minimum spanning tree which verifies whether the current topology is connected or not. To do so, we embed a trajectory estimate correction step based on graph theory algorithms. The proposed method was tested with several different underwater image sequences and results were presented to illustrate the performance.     

一种自动全景拼图的快速算法

基于柱面坐标的自动拼图方法计算简单快速,被广泛采用,但是该方法存在的两个问题：一是基于微分迭代的参数估计方法依赖于初值,容易落入局部极小;二是未考虑摄像机绕米轴的小角度旋转,导致拼接不准,提出一个改进的自动全景拼图鲁棒性快速算法,对于第1个问题,初始支 用重采样的小图像进行相关匹配,可以迅速得到接近最优欠妥 的参数初值,然后再用基于微分迭代的参数估计方法求精,对于第2个问题,在用基于微分迭代的参数估计方法求精时,增加对摄像机绕 光轴的小角度旋转参数估计,该算法简单快速,经实验适用于手持相机拍摄的图像。     

Determination of camera parameters for character motions using motion area

We propose a method to determine camera parameters for character motion, which considers the motion by itself. The basic idea is to approximately compute the area swept by the motion of the character’s links that are orthogonally projected onto the image plane, which we call “motion area”. Using the motion area, we can determine good fixed camera parameters and camera paths for a given character motion in the off-line or real-time camera control. In our experimental results, we demonstrate that our camera path generation algorithms can compute a smooth moving camera path while the camera effectively displays the dynamic features of character motion. Our methods can be easily used in combination with the method for generating occlusion-free camera paths. We expect that our methods can also be utilized by the general camera planning method as one of heuristics for measuring the visual quality of the scenes that include dynamically moving characters.     

Generalized parallel-perspective stereo mosaics from airborne video

In this paper, we present a new method for automatically and efficiently generating stereoscopic mosaics by seamless registration of images collected by a video camera mounted on an airborne platform. Using a parallel-perspective representation, a pair of geometrically registered stereo mosaics can be precisely constructed under quite general motion. A novel parallel ray interpolation for stereo mosaicing (PRISM) approach is proposed to make stereo mosaics seamless in the presence of obvious motion parallax and for rather arbitrary scenes. Parallel-perspective stereo mosaics generated with the PRISM method have better depth resolution than perspective stereo due to the adaptive baseline geometry. Moreover, unlike previous results showing that parallel-perspective stereo has a constant depth error, we conclude that the depth estimation error of stereo mosaics is in fact a linear function of the absolute depths of a scene. Experimental results on long video sequences are given.     

Gradient-Based Approach for Fine Registration of Panorama Images

This paper studies the application of gradient-based motion detection techniques (i.e., optical flow methods) for registration of adjacent images taken using a hand-held camera for the purposes of building a panorama. A general 8-parameter model or a more compact 3-parameter model is commonly used for transformation estimation. However, both models are approximations to the real situation when viewpoint position is not absolutely fixed but includes a small translation, and thus distortion and blurring are sometimes present in the final registration results. This paper proposes a new 5-parameter model that shows better result and has less strict requirement on good choice of unknown initial parameters. An analysis of disparity recovery range and its enlargement using Gaussian filter is also given.     

Robust Image Mosaicing of Soccer Videos using Self-Calibration and Line Tracking

In this paper we propose an accurate and robust image mosaicing method of soccer video taken from a rotating and zooming camera using line tracking and self-calibration. The mosaicing of soccer videos is not easy, because their playing fields are low textured and moving players are included in the fields. Our approach is to track line features on the playing fields. The line features are detected and tracked using a self-calibration technique for a rotating and zooming camera. To track line features efficiently, we propose a new line tracking algorithm, called camera parameter guided line tracking, which works even when the camera motion undergoes sudden changes. Since we do not need to know any model for scenes beforehand, the proposed algorithm can be easily extended to other video sources, as well as other sports videos. Experimental results show the accuracy and robustness of the algorithm. An application of mosaicing is also presented.     

视频人脸识别中判别性联合多流形分析

将基于视频的人脸识别转换为图像集识别问题,并提出两种流形来表示每个图像集:一种是类间流形,表示每个图像集的平均脸信息;另一种是类内流形,表示每个图像集的所有原始图像的信息.类间流形针对图像集之间的区别提取整体判别信息,作用是选出几个与待识别图像集较为相似的候选图像集.类内流形则考虑图像集内各原始图像之间的关系,负责从候选图像集中找出最为相似的一个.不同于现有的非线性流形方法中每幅图像对应流形中的一个点,采用分片技术学习两种流形的投影矩阵,每个分片对应流形中的一个点,所学到的特征更具有判别性,进而使流形边界更加清晰,同时解决了传统非线性流形方法中的角度偏差和不充分采样问题.还提出了与分片技术相匹配的流形之间的距离度量方法.最后在几个广为研究的数据集上进行了实验,结果表明:新方法的识别准确率高,尤其适用于不受控环境下的视频识别,而且不受视频段长短的影响.     

基于对数极坐标映射的图像拼接方法

图像拼接在基于图像的绘制、视频检索以及景物匹配等领域有着广泛的应用，为了获取大画面宽视场的场景表示，针对存在旋转及缩放变化的图像，提出了一种基于对数极坐标映射的图像拼接方法，该方法先将图像从笛卡儿坐标空间转换到对数极坐标空间，使得笛卡儿坐标空间中图像的旋转和缩放转换为对数极坐标空间中图像的二维平移，这样可直接利用相位相关法来估算出图像间的旋转角度和缩放因子，然后以此作为初值，再采用非线性最小化优化算法进一步求精图像间的运动参数来实现图像的配准，最后通过图像融合来实现图像的拼接。实验结果表明，该方法是有效的。     

Systems and Experiment Paper: Construction of Panoramic Image Mosaics with Global and Local Alignment

This paper presents a complete system for constructing panoramic image mosaics from sequences of images. Our mosaic representation associates a transformation matrix with each input image, rather than explicitly projecting all of the images onto a common surface (e.g., a cylinder). In particular, to construct a full view panorama, we introduce a rotational mosaic representation that associates a rotation matrix (and optionally a focal length) with each input image. A patch-based alignment algorithm is developed to quickly align two images given motion models. Techniques for estimating and refining camera focal lengths are also presented.In order to reduce accumulated registration errors, we apply global alignment (block adjustment) to the whole sequence of images, which results in an optimally registered image mosaic. To compensate for small amounts of motion parallax introduced by translations of the camera and other unmodeled distortions, we use a local alignment (deghosting) technique which warps each image based on the results of pairwise local image registrations. By combining both global and local alignment, we significantly improve the quality of our image mosaics, thereby enabling the creation of full view panoramic mosaics with hand-held cameras.We also present an inverse texture mapping algorithm for efficiently extracting environment maps from our panoramic image mosaics. By mapping the mosaic onto an arbitrary texture-mapped polyhedron surrounding the origin, we can explore the virtual environment using standard 3D graphics viewers and hardware without requiring special-purpose players.An erratum to this article can be found at     

摄像机简化模型对三维重构的影响--分析与实验

讨论了摄像机简化模型对三维重构的影响．主要结论有：当摄像机在两幅图像间的运动为纯平移运动时,从理论上证明了使用摄像机简化模型重构空间点与实际空间点之间满足仿射变换;当摄像机在两幅图像间的运动为一般刚体运动时,使用简化模型的重构只有在一定条件下才能较好地保持原物体的形状;在简化模型下,基于Kruppa方程的方法所估计的焦距精度不能满足三维重构的要求．实验结果表明：在三维重构中不能盲目地使用简化模型,必须对摄像机内参数进行全面标定．     

A robust hybrid image-based modeling system

This paper presents a new robust image-based modeling system for creating high-quality 3D models of complex objects from a sequence of unconstrained photographs. The images can be acquired by a video camera or hand-held digital camera without the need of camera calibration. In contrast to previous methods, we integrate correspondence-based and silhouette-based approaches, which significantly enhances the reconstruction of objects with few visual features (e.g., uni-colored objects) and improves surface smoothness. Our solution uses a mesh segmentation and charting approach in order to create a low-distortion mesh parameterization suitable for objects of arbitrary genus. A high-quality texture is produced by first parameterizing the reconstructed objects using a segmentation and charting approach, projecting suitable sections of input images onto the model, and combining them using a graph-cut technique. Holes in the texture due to surface patches without projecting input images are filled using a novel exemplar-based inpainting method which exploits appearance space attributes to improve patch search, and blends patches using Poisson-guided interpolation. We analyzed the effect of different algorithm parameters, and compared our system with a laser scanning-based reconstruction and existing commercial systems. Our results indicate that our system is robust, superior to other image-based modeling techniques, and can achieve a reconstruction quality visually not discernible from that of a laser scanner.     

A mosaicing scheme for pose-invariant face recognition.

Mosaicing entails the consolidation of information represented by multiple images through the application of a registration and blending procedure. We describe a face mosaicing scheme that generates a composite face image during enrollment based on the evidence provided by frontal and semiprofile face images of an individual. Face mosaicing obviates the need to store multiple face templates representing multiple poses of a user's face image. In the proposed scheme, the side profile images are aligned with the frontal image using a hierarchical registration algorithm that exploits neighborhood properties to determine the transformation relating the two images. Multiresolution splining is then used to blend the side profiles with the frontal image, thereby generating a composite face image of the user. A texture-based face recognition technique that is a slightly modified version of the C2 algorithm proposed by Serre et al. is used to compare a probe face image with the gallery face mosaic. Experiments conducted on three different databases indicate that face mosaicing, as described in this paper, offers significant benefits by accounting for the pose variations that are commonly observed in face images.     

一种改进的柱面全景视图生成方法

研究了相机存在绕光轴转动的情况下柱面全景图的生成，首先对柱面图像进行傅立叶变换，根据图像的傅立叶谱来估算出图像间的初始平移和旋转运动参数，再利用Levenberg-Marquardt非线性最小化方法逐步求精各运动参数，最后根据计算出的运动参数进行图像拼合获得柱面全景视图，实验结果表明该算法可以获得比较理想的拼接效果．