基于动态随机点立体图的立体视觉深度运动特性分析

利用动态随机点立体图,排除心理暗示线索对深度运动的影响,对立体视觉深度运动特性进行了研究.利用主观实验,分析了深度运动物体的运动位置、运动方向和运动速度等运动特性对于立体视觉舒适度(Stereo visual comfort,SVC)的影响, 并提出深度运动情况下的SVC与运动速度的预测模型.实验结果表明,动态随机点立体图中,运动物体的深度运动诱发了透视效果;在交叉视差(屏幕前)和非交叉视差(屏幕后)情况下,立体视觉深度运动导致的SVC不同.对计算得到的SVC的预测值和实测值进行相关性检测,三种深度运动的皮尔森相关系数(Pearson correlation coefficient,PCC)分别为0.956、0.972、0.977,充分表明该预测模型能够准确地预测SVC.     

A spatial hybrid motion compliant mechanism: Design and optimization

A hybrid motion system is defined as a mechanical system that combines a macro motion and a micro motion into one system to achieve a large motion and high resolution with fast response simultaneously. In this paper, a spatial hybrid motion mechanism with 3-DOFs is developed that integrates two types of motion through only one compliant mechanism: a macro motion driven by DC servomotors for large workspace and a micro motion driven by PZT actuators for high precision. A unique feature of the developed hybrid motion compliant mechanism is the elimination of coupling interaction between the macro motion and the micro motion by properly structure design. Three issues are addressed in this paper: (1) design principle and implementation of the hybrid motion mechanism; (2) kinematic analysis and dynamic analysis; and (3) optimization design of the hybrid motion mechanism. A spatial hybrid motion mechanism is developed and the optimization is conducted. The Taguchi method is used to identify significant parameters in the design optimization, and finite element analysis results verify the design principle of the parallel architecture for the hybrid motion mechanism.     

A Robust hierarchical motion estimation algorithm in noisy image sequences in the bispectrum domain

The present study describes a robust hierarchical motion estimation algorithm in noisy image sequences using the bispectrum. The motion can be characterized by an affine model and the parameters of an affine motion model are estimated by means third-order auto-bispectrum and cross-bispectrum measures. The basic components of this framework to obtain motion vectors are (i) pyramid construction, (ii) motion estimation and (iii) coarse-to-fine refinement. The entire motion is decomposed as a global and a local motion field, which helps accurately obtain high resolution estimates for the local motion field. Simulation results are presented and compared to those obtained from the phase correlation algorithm. The results demonstrate that the proposed method is more suited than the phase correlation algorithm to analyses complex noisy image sequences. On the other hand, our method produces smoother displacement vector field with a more accurate measure of object motion in different signal-to-noise ratio scenarios.     

Recognition of dynamic video contents with global probabilistic models of visual motion.

The exploitation of video data requires methods able to extract high-level information from the images. Video summarization, video retrieval, or video surveillance are examples of applications. In this paper, we tackle the challenging problem of recognizing dynamic video contents from low-level motion features. We adopt a statistical approach involving modeling, (supervised) learning, and classification issues. Because of the diversity of video content (even for a given class of events), we have to design appropriate models of visual motion and learn them from videos. We have defined original parsimonious global probabilistic motion models, both for the dominant image motion (assumed to be due to the camera motion) and the residual image motion (related to scene motion). Motion measurements include affine motion models to capture the camera motion and low-level local motion features to account for scene motion. Motion learning and recognition are solved using maximum likelihood criteria. To validate the interest of the proposed motion modeling and recognition framework, we report dynamic content recognition results on sports videos.     

An effective GM/LM-based video error concealment

Error concealment (EC) techniques are often utilized at decoder side to improve reconstructed videos, in case of some information is lost during transmission on a wireless or band-width limited communication channel. In this paper, a global motion/local motion (GM/LM)-based error concealment method is proposed. First, the correct-macro-blocks (CMBs) are classified into global motion compensated MBs and local motion compensated MBs adaptively. Then, an erroneous MB (EMB) is classified into one of the three types: global motion MB (GMB), local motion MB (LMB), and global/local overlapping MB (GLMB) according to the MB type information in its neighbors. For the EMB with its type, GMB is recovered using the global motion vector (GMV). The EMB with its type LMB is recovered using the average motion vector information. And for the MB with its type GLMB, a recursive boundary matching strategy is utilized to search an optimal recovering motion vector. Experimental results show the effectiveness of the proposed GM/LM-based error concealment method.     

运动法自动分割MPEG-4帧视频对象(VOP)

本文提出运动法实现MPEG-4帧视频对象（VOP）的自动分割。该方法的基本思想是利用前景的局部运动与背景的全局运动的差别检测出相应独立运动部件。针对独立运动部件（IMC）运动快慢的不同,该方法分解为适合较慢运动IMC的形态运动滤波器方法和适合较快运动IMC的变化检测掩码方法。处理结果表明该方法取得较好的分割效果。     

Fast motion estimation for surveillance video compression

In this article, novel approaches to perform efficient motion estimation specific to surveillance video compression are proposed. These includes (i) selective (ii) tracker-based and (iii) multi-frame-based motion estimation. In selective approach, motion vector search is performed for only those frames that contain some motion activity. In another approach, contrary to performing motion estimation on the encoder side, motion vectors are calculated using information of a surveillance video tracker. This approach is quicker but for some scenarios it degrades the visual perception of the video compared with selective approach. In an effort to speed up multi-frame motion estimation, we propose a fast multiple reference frames-based motion estimation technique for surveillance videos. Experimental evaluation shows that significant reduction in computational complexity can be achieved by applying the proposed strategies.     

Model evaluation and calibration for prospective respiratory motion correction in coronary MR angiography based on 3-D image registration

Image processing was used as a fundamental tool to derive motion information from magnetic resonance (MR) images, which was fed back into prospective respiratory motion correction during subsequent data acquisition to improve image quality in coronary MR angiography (CMRA) scans. This reduces motion artifacts in the images and, in addition, enables the usage of a broader gating window than commonly used today to increase the scan efficiency. The aim of the study reported in this paper was to find a suitable motion model to be used for respiratory motion correction in cardiac imaging and to develop a calibration procedure to adapt the motion model to the individual patient. At first, the performance of three motion models [one-dimensional translation in feet-head (FH) direction, three-dimensional (3-D) translation, and 3-D affine transformation] was tested in a small volunteer study. An elastic image registration algorithm was applied to 3-D MR images of the coronary vessels obtained at different respiratory levels. A strong intersubject variability was observed. The 3-D translation and affine transformation model were found to be superior over the conventional FH translation model used today. Furthermore, a new approach is presented, which utilizes a fast model-based image registration to extract motion information from time series of low-resolution 3-D MR images, which reflects the respiratory motion of the heart. The registration is based on a selectable global 3-D motion model (translation, rigid, or affine transformation). All 3-D MR images were registered with respect to end expiration. The resulting time series of model parameters were analyzed in combination with additionally acquired motion information from a diaphragmatic MR pencil-beam navigator to calibrate the respiratory motion model. To demonstrate the potential of a calibrated motion model for prospective motion correction in coronary imaging, the approach was tested in CMRA examinations in five volunteers.     

Multi-resolution motion estimation and compensation based on adjacent prediction of frame difference in wavelet domain

Aiming at the higher bit-rate occupation of motion vector encoding and more time load of full-searching strategies,a multi-resolution motion estimation and compensation algorithm based on adjacent prediction of frame difference was proposed.Differential motion detection was employed to image sequences and proper threshold was adopted to identify the connected region.Then the motion region was extracted to carry out motion estimation and motion compensation on it.The experiment results show that the encoding efficiency of motion vector is promoted,the complexity of motion es timation is reduced and the quality of the reconstruction image at the same bit-rate as Multi-Reso lution Motion Estimation (MRME) is improved.     

Computation and visualization of three-dimensional soft tissue motion in the orbit

This work presents a method to measure the soft tissue motion in three dimensions in the orbit during gaze. It has been shown that two-dimensional (2-D) quantification of soft tissue motion in the orbit is effective in the study of orbital anatomy and motion disorders. However, soft tissue motion is a three-dimensional (3-D) phenomenon and part of the kinematics is lost in any 2-D measurement. Therefore, T1-weighted magnetic resonance (MR) imaging volume sequences are acquired during gaze and soft tissue motion is quantified using a generalization of the Lucas and Kanade optical flow algorithm to three dimensions. New techniques have been developed for visualizing the 3-D flow field as a series of color-texture mapped 2-D slices or as a combination of volume rendering for display of the anatomy and scintillation rendering for the display of the motion field. We have studied the performance of the algorithm on four-dimensional volume sequences of synthetic motion, simulated motion of a static object imaged by MR, an MR-imaged rotating object and MR-imaged motion in the human orbit during gaze. The accuracy of the analysis is sufficient to characterize motion in the orbit and scintillation rendering is an effective visualization technique for 3-D motion in the orbit.     

A Battery‐Less Arbitrary Motion Sensing System Using Magnetic Repulsion‐Based Self‐Powered Motion Sensors and Hybrid Nanogenerator

Self‐powered arbitrary motion sensors are in high demand in the field of autonomous controlled systems. In this work, a magnetic repulsion‐assisted self‐powered motion sensor is integrated with a hybrid nanogenerator (MRSMS–HNG) as a battery‐less arbitrary motion sensing system. The proposed device can efficiently detect the motion parameters of a moving object along any arbitrary direction and simultaneously convert low frequency (<5 Hz) vibrations into useful electricity. The MRSMS–HNG consists of a central magnet for the electromagnetic (EMG)–triboelectric (TENG) nanogenerator and four side magnets for motion sensors. Because all the magnets are aligned in the same magnetization direction, the repulsive force owing to the movement of the central magnet actuates the side magnets to achieve self‐powered arbitrary motion sensing. These self‐powered motion sensors exhibit a high sensitivity of 981.33 mV g^?1 under linear motion excitation and have a tilting angle sensitivity of 9.83 mV deg^?1. The proposed device can deliver peak powers of 27 mW and 56 µW from the EMG and TENG, respectively. By integrating the self‐powered motion sensors and hybrid nanogenerator on a single device, real‐time wireless transmission of motion sensor data to a smartphone is successfully demonstrated, thus realizing a battery‐less arbitrary motion‐sensing system for future autonomous control applications.     

Global motion estimation from randomly selected motion vector groups and GM/LM based applications

Fast global motion estimation has been paid much attention in video compression and analysis. In this paper, a global motion estimation method is proposed by randomly selected motion vector groups in the compression domain directly. It is carried out by refining the centroid of the global motion parameters corresponding to the motion vector groups. Simulation results on different global motions show its effectiveness and robustness against noise and motion vector loss. Finally, two applications, namely the text occluded region recovery and the error concealment, are presented using the global motion/local motion information. Experimental results show the effectiveness of the proposed method. This work is supported in part by China National Natural Science Foundation (CNSF) under Project No.60572045, the Ministry of Education of China Ph. D. Program Foundation under Project No.20050698033, and by a Cooperation Project (2005.7- 2007.7) with Microsoft Research Asia.     

Computer Analysis of Heart Motion from Two-Dimensional Echocardiograms

In two-dimensional echocardiography the study of the motion of the heart, especially of the left ventricle, is of central interest. Although the clinician can see this motion on real-time two-dimensional echocardiograms, its quantification can still be greatly improved. This paper presents and tests a computer method to quantify the motion of the heart from digitized image sequences. This method computes on every point of an image the two-dimensional velocity vector which characterizes its motion from this image to the next. This approach has the following advantages: 1) border recognition algorithms are no longer needed, 2) motion is not restricted to its radial component, and 3) motion information is available on every point of the image.     

基于傅里叶干涉法的微结构离面运动测量

提出一种基于傅里叶变换的频闪显微干涉测试方法,对微谐振器和微悬臂梁的离面运动进行测试研究.微结构受激励产生周期离面运动,单个运动周期分解成若干运动相位,利用频闪照明获得不同运动相位的干涉图像,通过傅里叶变换计算出各自的包裹相位,并利用时间轴相位展开提取出微结构的离面周期运动信息.与时间相移干涉法相比,该方法只需在单个运动相位下采集1幅干涉图像,减少了干涉图像采集的时间.对比实验结果表明,傅里叶干涉法的离面运动测量精度优于20 nm.     

机载平台6-D运动误差对LiDAR点云质量的影响比较

直升机载荷平台6-D（Six-Dimensional）运动误差（即飞行轨迹和姿态角运动误差）对机载LiDAR点云质量影响显著,进而影响三维重建模型精度。分析各运动误差对点云质量的影响特点,对于有针对性地消除各运动误差影响、有效提高机载LiDAR三维成像产品精度具有重要意义。建立了机载激光扫描脚点三维空间位置偏差与机载平台六方位运动误差之间的传递关系;采用数值仿真,定量比较了六方位运动误差对激光点云密度分布和的影响,获得了六方位运动误差的影响特点及规律。仿真结果表明,直升机载荷平台的三个姿态角运动误差对点云密度的影响更显著,且随飞行高度的增大而增大,而三个飞行轨迹运动误差的影响相对较小。     

Motion planning for computer controlled automata

The motion planning of Computer Controlled Automata (CCA) is described. We consider two steps for the motion planning: (1) design of rough patterns of motion and (2) modification of the patterns iteratively to generate the desired motion. A real-time planning method for a robot task, which has been developed by the authors, is applied as the first step. Using this method, by operating a joystick, a human operator can generate a trajectory for the CCA while monitoring the actual motion. To accurately modify inadequate motion, in the second step, a CAD system is developed. Tools for the CAD system are described, and then the effectiveness is demonstrated using an experimental example.     

A Principal Component Clustering Approach to Object-Oriented Motion Segmentation and Estimation

This paper presents a framework for object-oriented scene segmentation in video, which uses motion as the major characteristic to distinguish different moving objects and then to segment the scene into object regions. From the feature block (FB) correspondences through at least two frames obtained via a tracking algorithm, the reference feature measurement matrix and feature displacement matrix are formed. We propose a technique for initial motion clustering of the FBs, in which the principal components (PC) of the two matrices are adopted as the motion features. The motion features have several advantages: (1) They are low-dimensional (2-dim). (2) They preserve well both the spatial closeness and the motion similarity of their corresponding FBs. (3) They tend to form distinctive clusters in the feature space, thus allowing simple clustering schemes to be applied. The Expectation-Maximization (EM) algorithm is applied for clustering the motion features. For those scenes involving mainly the camera motion, the PC-based motion features will exhibit nearly parallel lines in the feature space. This facilitates a simple and yet effective layer extraction scheme. The final motion-based segmentation involves labeling of all the blocks in the frame. The EM algorithm is again applied to minimize an energy function which takes motion consistency and neighborhood-sensitivity into account. The proposed algorithm has been applied to several test sequences and the simulation results suggest a promising potential for video applications.     

Complex-subband transform for subband-based motionestimation/compensation and coding

This paper introduces the complex subband transform (CST) that can be applied for both subband signal decomposition and motion estimation, which are the two major processes in subband-based image sequence coding. In the experiments, we compare the CST-based subband motion compensation with conventional block matching motion compensation, and find that the former has (i) higher peak signal-to-noise ratio (PSNR) of the reconstructed images and (ii) lower prediction error entropy of the motion vectors.     

Analysis of spatial transform motion estimation with overlappedcompensation and fractional-pixel accuracy

The authors investigate how the performance of spatial transform motion estimation can be significantly improved by incorporating overlapped compensation and fractional-pixel accuracy. An overlapped spatial transformation (OST) motion model is developed, which successfully addresses the inability of the conventional block matching technique to compensate for complex motion and inside-block motion field discontinuities. Simulation results show that the motion compensated prediction error of this method is reduced by 1.1 dB, compared with the conventional overlapped block matching motion estimation, for the same generated motion vectors overhead. To improve the performance, the overlap must be used in both the motion estimation and compensation processes. Further improvement can be obtained using half-pixel precision motion vectors. However, this improvement is comparatively less than the gain of conventional block matching from a half-pixel search