A motion and illumination resilient framework for automatic shot boundary detection

Detecting and locating a desired information in hefty amount of video data through manual procedure is very cumbersome. This necessitates segregation of large video into shots and finding the boundary between the shots. But shot boundary detection problem is unable to achieve satisfactory performance for video sequences consisting of flash light and complex object/camera motion. The proposed method is intended for recognising abrupt boundary between shots in the presence of motion and illumination change in an automatic way. Typically any scene change detection algorithm assimilates time separation in a shot resemblance metric. In this communication, absolute sum gradient orientation feature difference is matched to automatically generated threshold for sensing a cut. Experimental study on TRECVid 2001 data set and other publicly available data set certifies the potentiality of the proposed scheme that identifies scene boundaries efficiently, in a complex environment while preserving a good trade-off between recall and precision measure.     

Shot boundary detection in the presence of fire flicker and explosion using stationary wavelet transform

Detection of fire in video for fire alarm systems has been studied by many researchers, but detection of shot boundaries under fire, flicker and explosion (FFE) is one of the under-studied areas. In thriller movies, FFE occur more often than other special effects and lead to false detection of shot boundary. We tested major metrics used for detection of shot boundaries under FFE for various movies. It is observed that for almost all metrics, precision is low due to false positives caused by FFE. We propose an algorithm based on cross-correlation coefficient, stationary wavelet transform and combination of local and adaptive thresholds for detection of shot boundaries under FFE. The proposed algorithm is tested on three movies, and experimental results validate the effectiveness of our proposed method in terms of better recall and precision.     

基于ORB的镜头边界检测算法

场景中摄像机移动、对象运动、光亮突变等现象的存在导致现有镜头边界检测算法的顽健性不足,为了有效应对这些变化,提出一种基于ORB的镜头边界检测算法,算法通过计算图像帧之间ORB描述子的匹配程度进行镜头边界检测。在检测过程中使用特征点匹配数和匹配率对镜头边界的特点进行描述,并以相似度曲线描述图像帧之间的关系。实验结果表明,该算法可以有效解决上述问题造成的镜头误检、漏检,同时处理速度也获得了明显提升。     

Spatiotemporal motion boundary detection and motion boundary velocity estimation for tracking moving objects with a moving camera: a level sets PDEs approach with concurrent camera motion compensation

The purpose of this study is to investigate a method of tracking moving objects with a moving camera. This method estimates simultaneously the motion induced by camera movement. The problem is formulated as a Bayesian motion-based partitioning problem in the spatiotemporal domain of the image quence. An energy functional is derived from the Bayesian formulation. The Euler-Lagrange descent equations determine imultaneously an estimate of the image motion field induced by camera motion and an estimate of the spatiotemporal motion undary surface. The Euler-Lagrange equation corresponding to the surface is expressed as a level-set partial differential equation for topology independence and numerically stable implementation. The method can be initialized simply and can track multiple objects with nonsimultaneous motions. Velocities on motion boundaries can be estimated from geometrical properties of the motion boundary. Several examples of experimental verification are given using synthetic and real-image sequences.     

人脸图像检测与正规化的研究

人脸图像检测在实际运行中,复杂的背景、和人脸选择位置与大小都会影响到人脸识别率。为了克服这些因素并减少环境的干扰,设计了一种人脸图像检测与正规化的方法,详细论述了实现的关键技术。通过实验表明,人脸图像识别率和速度都有很大的改善,满足了实际环境中实时处理的需要。     

基于照明缺陷的光源照明系统图像检测控制电路设计

在目前的机器视觉应用系统中,光源与照明是整个系统的关键问题,不同照明方式都存在一定的缺陷特征。为了满足图像采集检测精度要求,针对不同照明方式缺陷特征,设计光源图像检测控制电路。采用单片机开关电源芯片作为主控芯片,设计LED光源图像检测背光控制电路,由电压转换、恒流控制以及背光调整等电路部分组成,电路结构简洁,简化电路设计。经过测试,控制电路效率高,满足图像采集需求。     

Image detection in the presence of speckle

Detection of binary images is considered in the presence of both speckle and additive noise. The detector performance has been evaluated in the presence of speckle as well as in the absence of it. It is observed that the presence of speckle increases the probability of error appreciably even at high signal-to-noise ratios (SNR's).     

Line and boundary detection in speckle images

This paper considers the problem of detecting lines in speckle imagery, such as that produced by synthetic aperture radar (SAR) or ultrasound techniques. Using the physical principles that account for the speckle phenomenon, we derive the optimal detector for lines in fully developed speckle, and we compare the optimal detector to several suboptimal detection rules that are more computationally efficient. We show that when the noise is uncorrelated, a very simple suboptimal detection rule is nearly optimal, and that even in colored speckle, a related class of detectors can approach optimal performance. Finally, we also discuss the application of this technique to medical ultrasonic images, where the detection of tissue boundaries is considered as a problem of line detection.     

Signal detection in the presence of multiple-access noise

In this paper we address the mutual interference problems that arise as a result of many independent terminals simultaneously accessing a common channel. "Random code" bounds are used to show the existence of large signal sets for which any one signal can be reliably detected by matched filters despite the mutual interference. Two types of signal sets are considered: sets with a unique signature for every terminal and sets drawn from a small collection of distinct waveforms. The latter sets permit reductions in receiver complexity.     

R-wave detection in the presence of muscle artifacts

Ambulatory electrocardiogram (ECG) recordings from patients undergoing severe physical stress are corrupted by large muscle artifacts (EMG) and other noise sources, such as baseline drifts and currents induced by motion artifacts and electromechanical devices. A simple and reliable QRS filter and R-wave detectot unit, for use under moderate to low QRS signal-to-noise ratio conditions, is described. It is found that a narrow bandpass sampled data filter design with a center frequency and bandwidth equal to 4 Hz maximizes the QRS signal-to-noise ratio under such conditions. The detector includes automatic gain control and a differencing integrator for improved R-wave detection.     

A fast parametric motion estimation algorithm with illumination and lens distortion correction

Methods for estimating motion in video sequences that are based on the optical flow equation (OFE) assume that the scene illumination is uniform and that the imaging optics are ideal. When these assumptions are appropriate, these methods can be very accurate, but when they are not, the accuracy of the motion field drops off accordingly. This paper extends the models upon which the OFE methods are based to include irregular, time-varying illumination models and models for imperfect optics that introduce vignetting, gamma, and geometric warping, such as are likely to be found with inexpensive PC cameras. The resulting optimization framework estimates the motion parameters, illumination parameters, and camera parameters simultaneously. In some cases these models can lead to nonlinear equations which must be solved iteratively; in other cases, the resulting optimization problem is linear. For the former case an efficient, hierarchical, iterative framework is provided that can be used to implement the motion estimator.     

Signal detection in the presence of weakly dependent noise--I: Optimum detection

The problem of discrete-time signal detection in the presence of additive noise exhibiting a weak form of dependence is considered. A moving-average representation is used to model dependence in the noise sequence, and the degree of dependence is parameterized by the averaging weights. The weak-dependence model is then based on the situation in which terms depending to second or higher Order on the averaging weights can be considered to be negligible. Part I of this two-part study considers the problem of asymptotically efficient detection in this context for situations in which the noise statistics are known. An appropriate detector is sought by modifying the corresponding independent-noise detector structure in a way which does not increase detector complexity, and a corresponding weak-dependence design criterion is developed. The solution to this problem is then seen to be based on a linearly corrected version of the optimum independent-noise detection nonlinearity. The performance of this detector is compared to that of the corresponding optimum system for independent noise with the conclusion that performance gain is achieved by the proposed systems with no corresponding increase in complexity. Several specific examples are discussed to illustrate the types of noise environments for which this design technique is useful. Part II of this study will treat the problem of robust detection in the presence of weakly dependent noise.     

视频检索中的镜头边界检测

镜头边界检测是视频检索的关键技术。文中介绍了目前镜头边界检测国内外的研究成果。各检测方法的特点及其不足之处,并指出了发展方向。检测手段主要集中在像素域和压缩域中。其中在像素域中的检测方法主要包括：像素亮度匹配、直方图比较、基于块的技术、二次比较、基于运动矢量的技术、基于网络的技术、基于镶嵌的技术。压缩域中的方法主要包括：利用ＤＣＴ系数进行匹配、利用矢量量化的方法、利用子带分解的方法、利用运动矢量的     

基于光强变化场景的目标检测与跟踪新方法

为在光强变化场景下实现目标的检测与跟踪,研究了一种新方法。该方法综合集成了Vibe算法与粒子滤波算法的优点,通过在改进Vibe算法中引入光照补偿模型、重构粒子滤波模型,解决了2种方法对光强变化的自适应性难题;在局部三值模式(LTP)中建立了一种自适应阈值方法,并采用线性回归分类方法,实现了目标跟踪。通过开发相应程序并将所提新方法的结果与标准结果进行对比验证,验证结果表明：新方法的偏差小于文中其他3个对照方法的相应偏差,该方法对光强变化场景下的目标检测与跟踪研究有一定帮助。     

Noncoherent block detection in the presence of DC offset

In this paper, we deal with noncoherent detection of a digitally phasor block-modulated signal in the additive white Gaussian noise channel when a direct-current (DC) offset is present in the receiver baseband processing. By processing the received baseband signal block by block, a generalized linear transform is used to remove the offset prior to data detection, thereby releasing the succeeding detection process from the threat of DC offset. Operating on transform output blocks, a generalized maximum-likelihood scheme is developed for noncoherent data detection without a priori knowledge of channel amplitude and phase. When all the signaling blocks are confined within the space expanded by the basis vectors obtained from the onset-removal transform matrix, the proposed detection scheme can exploit the advantage of performing data detection and estimation on channel amplitude and phase jointly in the maximum-likelihood sense. It is analytically shown that the block detection scheme provides the bit error performance asymptotically approaching that of the corresponding ideal coherent phase-shift-keyed (PSK) detection in the absence of DC offset when the block length is increased. An iterative detection scheme is also modified from the block detection scheme to simplify the realization complexity. Both block and iterative detection schemes are shown to outperform the conventional training-sequence-aided PSK detection scheme under the same transmission throughput efficiency.     

Small-delay defect detection in the presence of process variations

Interconnect-based defects such as partial opens are becoming more prevalent in nanoscale designs. These are latent defects that affect circuit reliability and can be modeled as small-delay defects. Detecting such defects therefore requires faster than at-speed test clocks. In the paper we analyze the uncertainty introduced by process variations in detecting these defects. We propose new path selection algorithms that increase the probability of defect detection by taking into account the variability in path delays. Our results show that the new technique detects much smaller defects than the traditional approach of selecting the longest paths for test.     

The estimation of the direction of object image motion in the presence of background

The maximum likelihood algorithm for estimating the motion direction of nonuniform image of space-extended object for the applicative model of interaction between the useful image and background has been synthesized and analyzed.     

Determination of the grain boundary recombination velocity in polycrystalline silicon as a function of illumination from photoconductance measurements

The grain boundary recombination velocity of polycrystalline Si is separated from bulk effects and its value is determined with practically no assumption of numerical values for any parameter other than the minority carrier diffusion coefficient. The method used utilizes photoconductance measurements taken by the scanning laser spot technique. It is found that, for the illumination levels used, there is a transition from low level to high-level injection of minority carriers, and this transition is used to estimate the quasi-Fermi level separation. The recombination velocity S, ranging in value from 5000 to 17000 cm/sec, is thus presented both as a function of the illumination level as well as of the quasi-Fermi level separation ΔE_f. It is found that S increases monotonically with illumination and does not saturate, even at the high light concentrations used.     

Efficient detection with arrays in the presence of angular spreading

The spatial channel in applications such as radar, sonar, and wireless communications is typically characterized by complex signal scattering leading to multiple signal components arriving at the array from a spread of angles. This multipath angle spread is well known to lead to loss of spatial signal coherence, requiring complicated combining schemes to achieve optimal performance, particularly when the signal is partially coherent across the receiving array. We show that the discrete Fourier transform serves as an efficient, robust, and asymptotically optimal spatial combiner for uniform linear arrays (ULAs) in multipath channels. In addition, the proposed spatial processing allows for convenient integration of conventional frequency-domain methods for angle-of-arrival searches. Simulation results show that the proposed combining scheme provides near-optimal performance at significantly less computation, even for arrays of moderate size.