三焦点张量重投影视频稳像算法

目的 目前,特征点轨迹稳像算法无法兼顾轨迹长度、鲁棒性及轨迹利用率,因此容易造成该类算法的视频稳像结果扭曲失真或者局部不稳。针对此问题,提出基于三焦点张量重投影的特征点轨迹稳像算法。方法 利用三焦点张量构建长虚拟轨迹,通过平滑虚拟轨迹定义稳定视图,然后利用三焦点张量将实特征点重投影到稳定视图,以此实现实特征点轨迹的平滑,最后利用网格变形生成稳定帧。结果 对大量不同类型的视频进行稳像效果测试,并且与典型的特征点轨迹稳像算法以及商业软件进行稳像效果对比,其中包括基于轨迹增长的稳像算法、基于对极几何点转移的稳像算法以及商业软件Warp Stabilizer。本文算法的轨迹长度要求低、轨迹利用率高以及鲁棒性好,对于92%剧烈抖动的视频,稳像效果优于基于轨迹增长的稳像算法;对于93%缺乏长轨迹的视频以及71.4%存在滚动快门失真的视频,稳像效果优于Warp Stabilizer;而与基于对极几何点转移的稳像算法相比,退化情况更少,可避免摄像机阶段性静止、摄像机纯旋转等情况带来的算法失效问题。结论 本文算法对摄像机运动模式和场景深度限制少,不仅适宜处理缺少视差、场景结构非平面、滚动快门失真等常见的视频稳像问题,而且在摄像机摇头、运动模糊、剧烈抖动等长轨迹缺乏的情况下,依然能取得较好的稳像效果,但该算法的时间性能还有所不足。     

Calibration-free augmented reality in perspective

This paper deals with video-based augmented reality and proposes an algorithm for augmenting a real video sequence with views of graphics objects without metric calibration of the video camera by representing the motion of the video camera in projective space. A virtual camera, by which views of graphics objects are generated, is attached to a real camera by specifying image locations of the world coordinate system of the virtual world. The virtual camera is decomposed into calibration and motion components in order to make full use of graphics tools. The projective motion of the real camera recovered from image matches has the function of transferring the virtual camera and makes the virtual camera move according to the motion of the real camera. The virtual camera also follows the change of the internal parameters of the real camera. This paper shows the theoretical and experimental results of our application of nonmetric vision to augmented reality     

一种基于球场模型的广播足球视频摄像机自动定标方法

随着足球视频语义内容分析和理解、自动视频索引、虚拟增强现实表示等研究的不断深入,摄像机定标技术扮演了越来越重要的角色.基于此,提出了一种基于球场模型的广播足球视频摄像机自动定标算法,该算法建立在所定义的球场模型基础之上,首先通过改进的球场线探测算法得到球场平面的特征点,并求解摄像机同形 (Homography)矩阵,然后,利用所求解的同形矩阵来定位球门,得到球门平面的两个特征点,最后根据基于K均值聚类和Hough-like搜索的方法来得到最优的摄像机内外参数.初步的实验结果表明,依据本文算法所求解的摄像机参数最优值相比初始值精确度更高,并且其在连续帧中也更加稳定.     

即时全变差优化的低延时视频稳像方法

目的 传统的视频稳像方法为了获得理想的稳像效果,一般耗费较多的计算时间,且存在较长的延时。针对此问题,提出一种即时全变差优化的低延时视频稳像方法。方法 首先利用特征点检测和匹配计算帧间单应变换,得到抖动视频的运动路径;然后通过即时全变差优化方法对抖动路径进行平滑优化,获得稳定的运动路径;最后通过运动补偿,生成稳定的视频。结果 对公共视频数据集中的抖动视频进行稳像效果测试,并与当前稳像效果较好的几种稳像算法和商业软件进行效果和时间对比。在时间方面,统计了不同方法的每帧平均消耗时间和处理延迟帧数,不同于后期处理方法需要得到大部分视频帧才能够进行计算,本文算法能够在只有一帧延时的情况下获得最终的稳像结果,相比于MeshFlow方法有15%左右的速度提升;在稳像效果方面,计算了不同方法稳像后的视频扭曲率和裁剪率,并邀请非专业用户进行了稳定程度的主观判断,本文算法的实验结果并不输于目前被公认较好的3种后期稳像方法,优于Kalman滤波方法。结论 本文所提稳像方法能够兼顾速度和有效性,相对于传统方法,更适合低延时要求的应用场景。     

Registering real and virtual imagery

Registering a virtual scene with a real scene captured by a video camera has a number of applications including visually guided robotic navigation, surveillance, military training and operation. The fundamental problem involves several challenging research issues including finding corresponding points between the virtual and the real scene and camera calibration. This paper presents our research in defining and mapping a set of reliable image features for registering the two imageries, extracting and selecting reliable control points for the construction of intrinsic and extrinsic camera parameters. A number of innovative algorithms are presented followed by extensive experimental analysis. An application of registering virtual database image with video image is presented. The algorithms we developed for calculating and matching linear structured features and selecting of reliable control points are applicable to image registration beyond virtual and real imageries.     

抗相机运动干扰的欧拉视频振动检测

相机运动的干扰是造成视频振动检测误差的重要原因。针对该问题,提出一种互抑制一致采样方法,对视频中的振动信号和相机运动信号实现有效分离,从而提高视频振动检测的可靠性。通过SURF（加速稳健特征）算法提取候选的特征点,并设计了振动与相机运动的互抑制测度,对候选的特征点进行分离,以获得相机运动的特征点。根据相机运动特征点对视频图像进行配准,以获得去除相机运动干扰的视频序列。对稳定相机的视频序列,采用欧拉视频振动检测方法获得振动频率。自行采集了不同相机运动下的视频,并针对互抑制测度的参数进行估计。通过对测试集数据进行验证,得到的振动频率准确率优于现有的非接触振动检测方法。     

摄像机自标定算法在虚拟演播室中的应用

本文就摄像机自标定算法进行了分析,在虚拟演播环境中,提出了基于平面点的标定算法,采用自己设计的实验方法,计算出了摄像机的内参数,结果证明能满足虚拟演播室中摄像机标定的精度。     

基于DSP的运动目标跟踪系统

描述了一种以TMS320C6701数字信号处理器为核心的高速图像处理板和图像实时采集卡及摄像头构成的实时运动跟踪系统。在对采集的实时图像序列进行如十预处理后．采用了金字塔结构的图像存储方式和特征点跟踪算法埘运动目标进行跟踪．通过对特征点的运算得到目标运动的偏差怍为摄像头运动的参数,是后根据这些参数控制摄像云台持续跟踪运动目标的移动,最后还给出了在复杂背景下跟踪人体的实验结果。     

Inside looking out camera pose estimation for virtual studio

This paper studies the inside looking out camera pose estimation for the virtual studio. The camera pose estimation process, the process of estimating a camera’s extrinsic parameters, is based on closed-form geometrical approaches which use the benefit of simple corner detection of 3D cubic-like virtual studio landmarks. We first look at the effective parameters of the camera pose estimation process for the virtual studio. Our studies include all characteristic landmark parameters like landmark lengths, landmark corner angles and their installation position errors and some camera parameters like lens focal length and CCD resolution. Through computer simulation we investigate and analyze all these parameters’ efficiency in camera extrinsic parameters, including camera rotation and position matrixes. Based on this work, we found that the camera translation vector is affected more than other camera extrinsic parameters because of the noise of effective camera pose estimation parameters. Therefore, we present a novel iterative geometrical noise cancellation method for the closed-form camera pose estimation process. This is based on the collinearity theory that reduces the estimation error of the camera translation vector, which plays a major role in camera extrinsic parameters estimation errors. To validate our method, we test it in a complete virtual studio simulation. Our simulation results show that they are in the same order as those of some commercial systems, such as the BBC and InterSense IS-1200 VisTracker.     

基于背景配准的矿井危险区域视频目标检测算法

针对矿井危险区域视频监控视场背景复杂,难以实现视频目标精确提取的问题,提出了一种基于背景配准的视频目标检测算法。该算法实现步骤:提取SIFT特征点,计算特征点区域H-S光流矢量;通过区域运动特性分析提取出背景运动区域,对背景运动区域特征点做帧间匹配;计算仿射参数,配准差分后提取出精确的目标区域。实验结果表明,该算法能够去除前景目标特征点对背景配准的影响,可获得较为精确的目标区域。     

Real-time camera motion tracking in planar view scenarios

We propose a novel method for real-time camera motion tracking in planar view scenarios. This method relies on the geometry of a tripod, an initial estimation of camera pose for the first video frame and a primitive tracking procedure. This process uses lines and circles as primitives, which are extracted applying classification and regression tree. We have applied the proposed method to high-definition videos of soccer matches. Experimental results prove that our proposal can be applied to processing high-definition video in real time. We validate the procedure by inserting virtual content in the video sequence.     

Low-power DSP system for real-time correction of fish-eye cameras in automotive driver assistance applications

The development of an embedded system for real-time correction of fish-eye effect is presented. The fish-eye lens is applied to driver assistance video systems because of its wide-angled view. A large field of view can reduce the number of cameras needed for video system and their cost, installation, maintenance and wiring issues. On the other hand, this lens causes inherent radial distortion to image that has to be corrected in real-time with a low-cost and low-power processing platform. This paper proposes a solution that can be easily adapted to different types of lens and camera, and meets real-time constraints with a power budget within 100 mW and a board size of few cm². Starting from mathematical equations, given by the geometrical optics, a state-of-the-art correction method is presented, then optimizations are introduced at different levels: algorithmic level, where a real-time correction parameter calculation avoids extra non-volatile off-chip memory cards; data transfer level, where a new pixel pair management reduces memory access and storage burden; HW-SW implementation level, where a low-power board has been developed and tested in real automotive scenarios. Other applications of the developed system, such as multi-camera and multi-dimensional video systems, are finally presented.     

增强现实中的摄像机径向畸变校正

增强现实系统中,有效地进行摄像机镜头畸变校正对提高虚拟环境的精确性具有重要意义.首先提出一种基于成像几何的畸变校正方法,采用带有一阶径向畸变的摄像机模型,对镜头径向畸变进行校正,再根据校正后的图像计算摄像机投影矩阵.实验表明,基于成像几何的畸变校正算法具有较高的畸变校正精度,640×480的图像中,最大畸变量达90多个像素.与利用理想针孔摄像机模型得到的增强现实环境相比,畸变校正后得到的叠加结果更为精确.     

基于加速稳健特征算法的监控摄像头视频融合技术

视频监控摄像头在现代安防中起到了不可替代的作用,为适应更多环境,摄像头技术也一直在不断发展.本文提出了一种可实现多摄像头画面实时拼接的技术设计方案:基于加速稳健特征算法,实现对视频单帧画面间的特征点进行提取及拼接;使用FFmpeg(Fast Forward Mpeg)媒体处理库进行视频摄像头媒体流文件的分解及最终融合视...     

Optimal feature points for tracking multiple moving objects in active camera model

Object tracking is an important task in computer vision that is essential for higher level vision applications such as surveillance systems, human-computer interaction, industrial control, smart compression of video, and robotics. Tracking, however, cannot be easily accomplished due to challenges such as real-time processing, occlusions, changes in intensity, abrupt motions, variety of objects, and mobile platforms. In this paper, we propose a new method to estimate and eliminate the camera motion in mobile platforms, and accordingly, we propose a set of optimal feature points for accurate tracking. Experimental results on different videos show that the proposed method estimates camera motion very well and eliminate its effect on tracking moving objects. And the use of optimal feature points results in a promising tracking. The proposed method in terms of accuracy and processing time has desirable results compared to the state-of-the-art methods.     

基于真实环境图象的三维动态仿真系统研究

针对在城市规划中,建筑设计方案的计算机三维图形与真实环境图象进行匹配及合成的问题,研究和提出了一种基于摄影测量学返透视原理的,对实际环境摄像经抽样采集的图象序列进行亮度、方差及平均色度合成的图象分析方法,并研究了一种基于单象空间后方交会解析摄影测量技术一阶渐近迭代计算的求解虚拟摄像参数的算法,同时提出了基于关键帧技术的适合于图象合成时,计算分割区域随时间变化的动态掩模算法,还在太阳系行星运动规律的基础上,建立了适合于计算机虚拟三维世界坐标系的日照模型,以及相应的求解任意时刻、任意经纬度虚拟世界坐标位置处的虚拟太阳光源方向和强度的算法。这些算法已被应用到基于真实环境图象的三维动态仿真系统中,实验结果表明,这些算法是行这有效的。     

基于直线投影特征的镜头畸变校正方法

针对摄像机镜头畸变校正方法的简便和快速问题,设计了基于直线投影特征的校正方法。介绍了镜头主要畸变产生原因和畸变模型;给出直线三点在理想投影下的关系,确定了适应度函数,利用遗传算法得到了畸变参数组最优解。基于matlab软件编写校正程序,并进行了实验验证。实验表明,利用畸变参数组的最优解能够实现图像畸变校正,效果较好。该标定方法只需场景内有直线存在即可实现对摄像机镜头畸变参数校正,方法所需实验条件简单,程序简便,便于现场快速校正。     

Tracking and Motion Estimation of the Articulated Object: a Hierarchical Kalman Filter Approach

Real-time motion capture plays a very important role in various applications, such as 3D interface for virtual reality systems, digital puppetry, and real-time character animation. In this paper we challenge the problem of estimating and recognizing the motion of articulated objects using theoptical motion capturetechnique. In addition, we present an effective method to control the articulated human figure in realtime.The heart of this problem is the estimation of 3D motion and posture of an articulated, volumetric object using feature points from a sequence of multiple perspective views. Under some moderate assumptions such as smooth motion and known initial posture, we develop a model-based technique for the recovery of the 3D location and motion of a rigid object using a variation of Kalman filter. The posture of the 3D volumatric model is updated by the 2D image flow of the feature points for all views. Two novel concepts – the hierarchical Kalman filter (KHF) and the adaptive hierarchical structure (AHS) incorporating the kinematic properties of the articulated object – are proposed to extend our formulation for the rigid object to the articulated one. Our formulation also allows us to avoid two classic problems in 3D tracking: the multi-view correspondence problem, and the occlusion problem. By adding more cameras and placing them appropriately, our approach can deal with the motion of the object in a very wide area. Furthermore, multiple objects can be handled by managing multiple AHSs and processing multiple HKFs.We show the validity of our approach using the synthetic data acquired simultaneously from the multiple virtual camera in a virtual environment (VE) and real data derived from a moving light display with walking motion. The results confirm that the model-based algorithm works well on the tracking of multiple rigid objects.     

基于视频的静止虚拟摄像机生成

虚拟摄像机的生成是虚拟广告系统中一项关键技术,提出一种静止虚拟摄像机生成方法。首先,在视频图像中自动检测比赛场地的特征点,然后根据特征点在图像坐标系与世界坐标系上的匹配关系,利用摄像机定标技术计算出真实摄像机的内外参数,接着把摄像机的内参数和外参数分别转换为虚拟摄像机的视点转换矩阵和投影矩阵,最后在此虚拟摄像机下对虚拟场景进行渲染,把渲染出的图像插入到视频中。实验结果表明该方法简单、有效、易实现。     

基于时间一致性局部颜色特征的无纹理3D物体实时跟踪

针对无纹理3D物体跟踪算法在复杂背景和运动模糊的情况下容易跟踪失败、跟踪速度难以达到强实时等问题,提出一种基于时间一致性局部颜色特征的3D物体实时跟踪算法.首先在物体3D模型投影轮廓法向搜索线上计算像素颜色的加权均值作为局部颜色特征,增强颜色特征在复杂环境中的表征能力,并对局部颜色特征进行时间一致性更新,剔除前景背景颜色相似的局部颜色特征,以避免相似前景背景颜色导致的跟踪失败;然后定义基于局部颜色特征的能量函数,并推导该能量函数的解析导函数;最后改进了优化物体姿态的高斯牛顿法,通过添加阻尼参数防止姿态优化陷入局部极值,提高姿态估计精度和跟踪速度.实验使用7组测试视频验证文中算法,结果表明,该算法能更有效地克服复杂背景和运动模糊的干扰,在未使用并行计算的前提下可实现强实时跟踪.