共查询到20条相似文献,搜索用时 15 毫秒
1.
2.
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 相似文献
3.
4.
5.
在摄像机运动的情况下,提出了一种基于光流场分割和Canny边缘算子融合技术的运动目标检测方法.这种方法可分为三步:第一步利用运动的内极线约束和C-均值聚类算法完成目标区域的分割,并获得分割图;第二步在分割图中利用Canny边缘算子获得细化的目标区域边缘图;第三步根据光流场中的流速值完成分割图和边缘图的融合,并检测出完整的运动目标.实验表明,这种方法可以有效地从复杂自然场景的图像序列中检测出完整的运动目标. 相似文献
6.
7.
A semi-automatic seeded region growing algorithm for video object localization and tracking 总被引:12,自引:0,他引:12
This paper describes a semi-automatic method for moving object segmentation and tracking. This method is suitable when a few objects have to be tracked, while the camera moves and fixates on them. The user delineates approximately the initial locations in a selected frame and specifies the depth ordering of the objects to be tracked. First, motion-based segmentation is obtained through an initial application of a region growing algorithm. The partition map is sequentially tracked from frame to frame using motion compensation and location prediction. The segmentation map is obtained by the region growing algorithm. Translational motion is assumed for the moving objects, and local intensity or color average may be used as additional features. A post-processing procedure regularizes the object boundaries over time. 相似文献
8.
《IEEE transactions on image processing》2008,17(12):2403-2412
9.
10.
为了解决港口背景下红外运动目标检测中受背景干扰带来的误分割和误跟踪问题,提出了一种基于港口背景抑制和光流检测的红外运动目标检测方法。首先,通过对小波分解图像进行OTSU分割,得到天水线区域。然后使用多级滤波确定序列图像中港口背景的抑制基准点,并根据这些背景抑制基准点实现序列图像的港口背景抑制。最后,运用光流预测实现红外运动目标检测。通过对实际港口背景红外图像进行背景抑制和红外运动目标检测的实验,验证了所提方法的可行性和有效性。 相似文献
11.
Optical flow estimation and moving object segmentation based onmedian radial basis function network 总被引:1,自引:0,他引:1
Various approaches have been proposed for simultaneous optical flow estimation and segmentation in image sequences. In this study, the moving scene is decomposed into different regions with respect to their motion, by means of a pattern recognition scheme. The inputs of the proposed scheme are the feature vectors representing still image and motion information. Each class corresponds to a moving object. The classifier employed is the median radial basis function (MRBF) neural network. An error criterion function derived from the probability estimation theory and expressed as a function of the moving scene model is used as the cost function. Each basis function is activated by a certain image region. Marginal median and median of the absolute deviations from the median (MAD) estimators are employed for estimating the basis function parameters. The image regions associated with the basis functions are merged by the output units in order to identify moving objects. 相似文献
12.
If a somewhat fast moving object exists in a complicated tracking environment, snake’s nodes may fall into the inaccurate local minima. We propose a mean shift snake algorithm to solve this problem. However, if the object goes beyond the limits of mean shift snake module operation in suc- cessive sequences, mean shift snake’s nodes may also fall into the local minima in their moving to the new object position. This paper presents a motion compensation strategy by using particle filter; therefore a new Parti... 相似文献
13.
14.
15.
基于Snake活动轮廓模型的视频跟踪分割方法 总被引:4,自引:3,他引:1
基于Snake活动轮廓模型,采用时空融合的方式,根据短时间内相邻帧的运动趋势差异相似的前提,首先将视频序列分成若干个小段,每段有k帧视频,选取段内的前两帧为关键帧,通过运动检测的方式自动得到这两帧中运动对象的大致区域;然后进行帧内Snake演变,搜索精确轮廓;最后以关键帧间运动对象形心的运动矢量预测勾勒后续帧的初始轮廓,进行帧内Snake精确轮廓定位,从而实现所有帧的视频对象分割。相比于传统方法,本文方法克服了手动绘制初始轮廓的缺点,在空域对Snake贪婪方法进行了改进而且精确度高,速度快。实验表明,本文方法成功地实现了前后帧图像之间运动对象的对应匹配关系,并通过改进后的Snake贪婪方法得到了精确的分割结果。 相似文献
16.
在运动目标的实时检测中常用的方法是背景图像差分法,但因其缺乏背景图像随监视场景光照变化而及时更新的合理方法,限制了本方法的适应性.对此,本文首先提出了一种基于光流场等技术的自适应背景逼近更新方法,并根据彩色差值模型得到差分图像;然后引入Gauss模型实现运动目标的自适应阈值分割.实验结果表明:本文提出的背景更新方法可随着光照条件的变化实时、准确地更新背景图像,在此基础上提出的基于Gauss模型的自适应阈值分割方法可以实现运动目标的完整分割,这为运动目标的后续识别与理解奠定了基础. 相似文献
17.
空域视频场景监视中运动对象的实时检测与跟踪技术 总被引:3,自引:0,他引:3
本文分析了空域视频场景中运动对象实时检测、跟踪系统的模型。提出了一种在运动背景下实时检测与跟踪视频运动目标的技术。该方法首先进行背景的全局运动参数估计,并对背景进行补偿校正,将补偿校正后的相邻两帧进行差分检测。然后利用假设检验从差分图像中提取运动区域,利用遗传学方法在指定区域内确定最优分割门限,提取视频运动对象及其特征;最后利用线性预测器对目标进行匹配跟踪。在基于高速DSP的系统平台上的实验结果表明该方法取得了很好的效果。 相似文献
18.
利用光流法可以对视频中运动目标进行特征点跟踪,当目标存在较大尺度运动时,光流法图像一致性假设难以满足,导致特征点跟踪丢失。针对此问题,提出了一种基于Lucas-Kanade(L-K)金字塔光流算法的运动人体特征点跟踪方法。首先,利用帧间差分法得到帧差图像序列,获取行人的运动区域;然后用尺度不变特征变换(SIFT)算法检测选定初始帧中的特征点;最后运用L-K金字塔光流算法跟踪这些特征点在后续帧中的位置。实验结果表明,该算法对较大尺度运动的特征点跟踪有很好的效果,提高了跟踪的准确性。 相似文献
19.
Layered video representations are increasingly popular; see [2] for a recent review. Segmentation of moving objects is a key step for automating such representations. Current motion segmentation methods either fail to segment moving objects in low-textured regions or are computationally very expensive. This paper presents a computationally simple algorithm that segments moving objects, even in low-texture/low-contrast scenes. Our method infers the moving object templates directly from the image intensity values, rather than computing the motion field as an intermediate step. Our model takes into account the rigidity of the moving object and the occlusion of the background by the moving object. We formulate the segmentation problem as the minimization of a penalized likelihood cost function and present an algorithm to estimate all the unknown parameters: the motions, the template of the moving object, and the intensity levels of the object and of the background pixels. The cost function combines a maximum likelihood estimation term with a term that penalizes large templates. The minimization algorithm performs two alternate steps for which we derive closed-form solutions. Relaxation improves the convergence even when low texture makes it very challenging to segment the moving object from the background. Experiments demonstrate the good performance of our method. 相似文献
20.
Cheolkon Jung L.C. JiaoMaoguo Gong 《AEUE-International Journal of Electronics and Communications》2012,66(3):235-238
We provide a new motion segmentation method in image sequences based on gamma distribution. Motion segmentation is very important because it can be employed for video surveillance, object tracking, and action recognition. The Gaussian mixture model (GMM) has been widely used as a distribution model for motion segmentation. However, we found that the gamma distribution model is more suitable than the GMM for the optical flow based motion segmentation. Experimental results show that the proposed method is very effective in producing accurate motion segmentation results in image sequences. 相似文献