Accurate optical flow in noisy image sequences using flow adapted anisotropic diffusion

In this paper, we combine 3D anisotropic diffusion and motion estimation for image denoising and improvement of motion estimation. We compare different continuous isotropic nonlinear and anisotropic diffusion processes, which can be found in literature, with a process especially designed for image sequence denoising for motion estimation. All of these processes initially improve motion estimation due to reduction of noise and high frequencies. But while all the well known processes rapidly destroy or hallucinate motion information, the process brought forward here shows considerably less information loss or violation even at motion boundaries. We show the superior behavior of this process. Further we compare the performance of a standard finite difference diffusion scheme with several schemes using derivative filters optimized for rotation invariance. Using the discrete scheme with least smoothing artifacts we demonstrate the denoising capabilities of this approach. We exploit the motion estimation to derive an automatic stopping criterion.     

Tracking pylorus in ultrasonic image sequences with edge-based optical flow

Tracking pylorus in ultrasonic image sequences is an important step in the analysis of duodenogastric reflux (DGR). We propose a joint prediction and segmentation method (JPS) which combines optical flow with active contour to track pylorus. The goal of the proposed method is to improve the pyloric tracking accuracy by taking account of not only the connection information among edge points but also the spatio-temporal information among consecutive frames. The proposed method is compared with other four tracking methods by using both synthetic and real ultrasonic image sequences. Several numerical indexes: Hausdorff distance (HD), average distance (AD), mean edge distance (MED), and edge curvature (EC) have been calculated to evaluate the performance of each method. JPS achieves the minimum distance metrics (HD, AD, and MED) and a smaller EC. The experimental results indicate that JPS gives a better tracking performance than others by the best agreement with the gold curves while keeping the smoothness of the result.     

基于区域卷积神经网络和光流法的目标跟踪

为解决基于深度学习的在线目标跟踪算法速度慢的问题,设计并实现了一种基于区域卷积网络和光流法相结合的目标跟踪算法。该算法在T-1帧跟踪结果的基础上使用光流法计算跟踪目标的运动矢量计算出跟踪目标在T帧上的初选框,再将初选框区域作为区域卷积网络的输入,计算目标的精确跟踪结果。通过实验分析对比,算法对目标运动速度和形变具有很好的鲁棒性,并且跟踪速度可以达到50 frame/s。相较于在线跟踪算法,所提方法在满足较高的跟踪准确率的基础上大大提升了目标跟踪算法的速度。     

Automatic segmentation of echocardiographic sequences by active appearance motion models

A novel extension of active appearance models (AAMs) for automated border detection in echocardiographic image sequences is reported. The active appearance motion model (AAMM) technique allows fully automated robust and time-continuous delineation of left ventricular (LV) endocardial contours over the full heart cycle with good results. Nonlinear intensity normalization was developed and employed to accommodate ultrasound-specific intensity distributions. The method was trained and tested on 16-frame phase-normalized transthoracic four-chamber sequences of 129 unselected infarct patients, split randomly into a training set (n = 65) and a test set (n = 64). Borders were compared to expert drawn endocardial contours. On the test set, fully automated AAMM performed well in 97% of the cases (average distance between manual and automatic landmark points was 3.3 mm, comparable to human interobserver variabilities). The ultrasound-specific intensity normalization proved to be of great value for good results in echocardiograms. The AAMM was significantly more accurate than an equivalent set of two-dimensional AAMs.     

Cinematography sequences tracking by means of fingerprinting techniques

Video fingerprints are short features extracted from a video sequence in order to uniquely identify its visual content and its replicas. By advancing a new robust fingerprinting method, the present paper takes the challenge of designing an enabler for the use of Internet as a distribution tool in cinematography. In this respect, a 2D-DWT-based robust video fingerprinting method is designed so as to address two use cases, namely the retrieval of video content from a database and the tracking of in-theater camcorder recorded video content. A set of largest absolute value wavelet coefficients is considered as the fingerprint and a repeated statistical test is used as the matching procedure. The video dataset consists of two corpora, one for each use case. The first corpus regroups 3 h of heterogeneous original content (organized under the framework of the HD3D-IIO French national project) and of its attacked versions (a total of 21 h of video content). The second corpus consists of 3 h of heterogeneous content (i.e., HD3D-IIO corpus) and of 1 h of live camcorder recorded video content (a total of 4 h of video content). The inner 2D-DWT properties with respect to content-preserving attacks (such as linear filtering, sharpening, geometric, conversion to grayscale, small rotations, contrast changes, brightness changes, and live camcorder recording) ensure the following results: in the first use case, the probability of false alarm and missed detection are lower than 0.0005, precision and recall are higher than 0.97; in the second use case, the probability of false alarm is 0.00009, the probability of missed detection is lower than 0.0036, precision and recall are equal to 0.72.     

基于光流方程和目标匹配的视频图像目标跟踪方法

提出一种利用图像差分、局部光流法和目标匹配,实现视频对象目标提取和跟踪的方法.首先,对预处理后的图像进行差分;在差分的基础上,运用局部光流场对目标进行运动估计;对估计结果依据相似度进行聚类分析,消除小的非目标区域;当目标未发生剧烈变化时,更新目标模板,否则,利用已有目标模板进行匹配跟踪.实验结果验证了该算法的有效性,并实现了目标变形和部分遮挡时的稳定跟踪.     

精确制导系统中的目标跟踪与卡尔曼滤波

针对精确制导中的目标跟踪问题,应用卡尔曼滤波算法进行了仿真研究.该算法在建立基于卡尔曼滤波运动模型的基础上,通过测量获得运动目标角度及径向距离数据,然后根据推广卡尔曼滤波算法迭代估算出目标的位置.通过对仿真结果分析可得,该方法有良好的跟踪性能,卡尔曼滤波在精确制导系统的目标定位,跟踪等领域有着广泛的应用前景.     

Segmentation of video sequences and rate control

This paper deals with the relation between segmentation for coding and rate control. The efficiency of a segmentation-based coding scheme heavily relies on this step that defines how many and which regions have to be segmented. In this paper, we show that this problem can be formulated as a rate/distortion problem. The proposed solution not only controls the segmentation, but also defines the coding strategy to be used in each region. Together with the general approach, several simplified versions of the segmentation control are proposed and discussed.     

LK光流法的多信息融合目标跟踪算法研究

针对改善动态目标物体跟踪过程中特征点选取的准确性及实时性问题,提出一种基于LK光流法的多信息融合目标跟踪方法并设计相关算法。将Sift提取出的特征点作为初始特征点,结合Harris角点检测函数R值,通过设定阈值,从中选取出具有高对比度的特征点作为目标特征点,对其进行光流法跟踪;然后引入在线学习检测器,使得在跟踪器跟踪失败之后可以更新目标位置,以实现稳定、准确跟踪。实验的结果从动态目标识别所需时间、特征点的数量、交并比以及每秒处理的帧数几个方面进行比较分析,证明所提算法能够实现准确跟踪,且实时性强。     

Prediction and tracking of moving objects in image sequences

We employ a prediction model for moving object velocity and location estimation derived from Bayesian theory. The optical flow of a certain moving object depends on the history of its previous values. A joint optical flow estimation and moving object segmentation algorithm is used for the initialization of the tracking algorithm. The segmentation of the moving objects is determined by appropriately classifying the unlabeled and the occluding regions. Segmentation and optical flow tracking is used for predicting future frames.     

Wall position and thickness estimation from sequences of echocardiographic images

Presents a new method for endocardial (inner) and epicardial (outer) contour estimation from sequences of echocardiographic images. The framework herein introduced is fine-tuned for parasternal short axis views at the papillary muscle level. The underlying model is probabilistic; it captures the relevant features of the image generation physical mechanisms and of the heart morphology. Contour sequences are assumed to be two-dimensional noncausal first-order Markov random processes; each variable has a spatial index and a temporal index. The image pixels are modeled as Rayleigh distributed random variables with means depending on their positions (inside endocardium, between endocardium and pericardium, or outside pericardium). The complete probabilistic model is built under the Bayesian framework. As estimation criterion the maximum a posteriori (MAP) is adopted. To solve the optimization problem, one is led to (joint estimation of contours and distributions' parameters), the authors introduce an algorithm herein named iterative multigrid dynamic programming (IMDP). It is a fully data-driven scheme with no ad-hoc parameters. The method is implemented on an ordinary workstation, leading to computation times compatible with operational use. Experiments with simulated and real images are presented.     

Segmentation and tracking of moving objects for content-based videocoding

To enable content-based functionalities in video coding, a decomposition of the scene into physical objects is required. Such objects are normally not characterised by homogeneous colour, intensity, or optical flow. Therefore, conventional techniques based on these low-level features cannot perform the desired segmentation. The authors address segmentation and tracking of moving objects and present a new video object plane (VOP) segmentation algorithm that extracts semantically meaningful objects. A morphological motion filter detects physical objects by identifying areas that are moving differently from the background. A new filter criterion is introduced that measures the deviation of the estimated local motion from the synthesised global motion. A two-dimensional binary model is derived for the object of interest and tracked throughout the sequence by a Hausdorff object tracker. To accommodate for rotations and changes in shape, the model is updated every frame by a two-stage method that accounts for rigid and non-rigid moving parts of the object. The binary model then guides the actual VOP extraction, whereby a novel boundary post-processor ensures high boundary accuracy. Experimental results demonstrate the performance of the proposed algorithm     

Propagation and optical interaction of guided acoustic waves intwo-mode optical fibers

Acoustic modes propagating in cylindrical solid rods are considered. A review of the properties of several mode groups is given, and computed results are shown for a wide range of material properties. The lower mode of each group is relevant for an all-fiber-optic frequency shifter recently demonstrated. For these modes, dispersion relations, mode patterns, power relations, and acoustooptic coupling strength are calculated. Some experimental results are compared with the calculations, and alterations to improve the frequency shifter are proposed     

Dynamic tracking in interventional MRI using wavelet-encodedgradient-echo sequences

This work describes a newly developed magnetic resonance imaging (MRI) data-acquisition strategy which replaces the standard Fourier phase-encoding with the spatially localized coefficients of wavelet-encoding and offers a new technique for image guidance when combined with a dynamic tracking algorithm. By using this new technique, only a specific fraction of the entire raw data set needs to be updated and reconstructed to visualize the movement of an interventional device during an MR guided procedure. The combination of wavelet-encoding and a dynamic tracking algorithm was implemented in two-dimensional and three-dimensional gradient-echo sequences on a 0.2-T open C-arm-shaped MR system (Siemens, Erlangen Germany) and tested in phantom and in vitro experiments. When applying the wavelet-encoding direction parallel to the movement of a straight interventional device, only those spatially localized wavelet-coefficients mainly affected by the interventional device are updated. This led to potential increases of the image frame rate by a factor of up to seven     

Saliency model-based face segmentation and tracking in head-and-shoulder video sequences

In this paper, a novel face segmentation algorithm is proposed based on facial saliency map (FSM) for head-and-shoulder type video application. This method consists of three stages. The first stage is to generate the saliency map of input video image by our proposed facial attention model. In the second stage, a geometric model and an eye-map built from chrominance components are employed to localize the face region according to the saliency map. The third stage involves the adaptive boundary correction and the final face contour extraction. Based on the segmented result, an effective boundary saliency map (BSM) is then constructed, and applied for the tracking based segmentation of the successive frames. Experimental evaluation on test sequences shows that the proposed method is capable of segmenting the face area quite effectively.     

Segmentation for robust tracking in the presence of severe occlusion

Tracking an object in a sequence of images can fail due to partial occlusion or clutter. Robustness to occlusion can be increased by tracking the object as a set of "parts" such that not all of these are occluded at the same time. However, successful implementation of this idea hinges upon finding a suitable set of parts. In this paper we propose a novel segmentation, specifically designed to improve robustness against occlusion in the context of tracking. The main result shows that tracking the parts resulting from this segmentation outperforms both tracking parts obtained through traditional segmentations, and tracking the entire target. Additional results include a statistical analysis of the correlation between features of a part and tracking error, and identifying a cost function that exhibits a high degree of correlation with the tracking error.     

Efficient optical camera tracking in virtual sets

Optical tracking systems have become particularly popular in virtual studios applications tending to substitute electromechanical ones. However, optical systems are reported to be inferior in terms of accuracy in camera motion estimation. Moreover, marker-based approaches often cause problems in image/video compositing and impose undesirable constraints on camera movement, present work introduces a novel methodology for the construction of a two-tone blue screen, which allows the localization of camera in three-dimensional (3-D) space on the basis of the captured sequence. At the same time, a novel algorithm is presented for the extraction of camera's 3-D motion parameters based on 3-D-to-two-dimensional (2-D) line correspondences. Simulated experiments have been included to illustrate the performance of the proposed system.     

基于光闪烁法的烟气流速及流量的测量

提出了一种利用光闪烁技术监测工业管道烟 气排放的方法,在实际应用中具 有适应范围广、结构灵活和测量准确等特点。利用开源流体模拟软件 OpenFOAM对圆直管道内的流体进行了数值分析,构造网格数为526240,基于图形处理器(GPU )的高性能计算平台对流体的数值仿真 进行了并行加速,取得了3.493倍的加速比。描述了光闪烁法测量烟 气流速、流量的步骤,对实验室的模拟烟道内的烟气流 速和流量进行了测量,并与皮托管所测得的数据进行对比,得到了较为一致的结果。