Fast motion detection in compressed domain for video surveillance

A fast algorithm to detect motion in the compressed domain for video surveillance is presented. The algorithm partially decompresses the video bit stream and performs motion detection from its quantised discrete cosine transform coefficients. The very low computational cost makes this algorithm very useful when real-time motion detection has to be performed simultaneously in several video bit streams     

浅析警戒探测系统

利用作战平台上多种探测设备的探测数据进行多层次的融合从而获得全面、完整、精确的战场态势是警戒探测系统的主要目标。本文分析了警戒探测系统的构成、工作方式及主要应用模式。     

Multi-view and multi-plane data fusion for effective pedestrian detection in intelligent visual surveillance

For the robust detection of pedestrians in intelligent video surveillance, an approach to multi-view and multi-plane data fusion is proposed. Through the estimated homography, foreground regions are projected from multiple camera views to a reference view. To identify false-positive detections caused by foreground intersections of non-corresponding objects, the homographic transformations for a set of parallel planes, which are from the head plane to the ground, are applied. Multiple features including occupancy information and colour cues are extracted from such planes for joint decision-making. Experimental results on real world sequences have demonstrated the good performance of the proposed approach in pedestrian detection for intelligent visual surveillance.     

Robust real-time ship detection and tracking for visual surveillance of cage aquaculture

This paper presents a visual surveillance scheme for cage aquaculture that automatically detects and tracks ships (intruders). For ship detection and tracking, we propose a robust foreground detection and background updating to effectively reduce the influence of sea waves. Furthermore, we propose a fast 4-connected component labeling method to greatly reduce the computational cost associated with the conventional method. Wave ripples are removed from regions with ships. An improved full search algorithm based on adaptive template block matching with a wave ripple removal is presented to quickly, accurately, and reliably track overlapping ships whose scales change. Experimental results demonstrate that the proposed schemes have outstanding performance in ship detection and tracking. The proposed visual surveillance system for cage aquaculture triggers an alarm if intruders are detected. The security of cage aquaculture can be increased. The proposed visual surveillance can thus greatly help the popularization of cage aquaculture for ocean farming.     

Combined QRD-M and DFE detection technique for simple and efficient signal detection in MIMO-OFDM systems

An efficient MIMO signal detection technique with low complexity is presented for MIMO-OFDM systems. The proposed technique has a feature of combined QRD-M and DFE detection. In our detection technique with M transmit antennas, after QRD-M detection is executed for first T detection steps, DFE detection is executed for last M - T detection steps. This approach is simple and has low complexity, because the computations for QRD-M is limited by the newly adopted parameter T. From simulation results, the complexity of the proposed technique with 4 × 4 and T = 2 is reduced by 61% compared with that of the conventional QRD-M at the expense of about 0.7dB degradation of BER performance at BER=10⁻⁴. The simulations are executed in Ricean and Rayleigh channel models. And the simulation of proposed technique is executed by using estimated channel. Through the simulations, it is ascertained that the proposed detection can be used for Ricean and Rayleigh channel models as well as estimated channel.     

视频监控系统中的行人及其面部侦测研究

采用集成H．264硬件编解码视频处理单元Hi3512来设计视频监控系统。并探讨行人目标的自动侦测问题。在对视频图像进行形态学分析的基础上,利用背景差方法实现运动目标区域的粗提取,通过阴影去除算法实现运动目标的精确定位,再利用连续均值量化变换（SuccessiveMeanQuantizafionTransform,SMQT）算法实现运动区域灰度图像的增强处理,然后利用SNoW（SparseNetworkofWinnows）分类算法实现行人及其人脸部位的侦测。实验结果表明,所采用方法能够自动检测出监控区域的行人目标及其面部信息,可有效地应用于无人值守视频监控场合。     

Automatic detection of ship target and motion direction in visual images

In this article, we focus on automatic ship target detection in visual images. The proposed approach consists of two stages. At the first stage, emphasis is placed on sea background suppression. A pre-processing technique is studied based on mean-shift smoothing algorithm. In this process, the improvement is that we associate the range bandwidth of mean-shift with local image properties, thus achieve the purpose of suppressing sea background while protecting ship target. At the second stage, a hierarchical ship target detection approach is developed. To begin with, region-of-interest (ROI) of ship target is coarsely identified via salient edge regions extraction. Then main body of ship target is located by projection, prior spatial structure information of ship target is used for further ROI refinement. After that, a post-processing procedure based on colour features is presented to obtain final detection results. One advantage of the proposed method is that motion direction of the ship target can also be estimated, which could provide important information for ship target tracking and monitoring. Tested on real visual ship target images supplied by the co-operator, experimental results show that the proposed algorithm can effectively detect big ship targets and its motion direction with various backgrounds in visual images.     

视觉注意机制的运动方向异常检测方法

针对传统运动方向异常检测方法需要人工参与、智能化较低等缺点,提出了一种新的基于视觉注意机制的运动方向异常检测方法。该方法通过合成源图像的空间导数图与时间导数图获得运动边缘,求取沿空间各方位分布的运动方向特征图。在此基础上,利用所提出的基于运动区域面积的归一化方法对得到的每一幅特征图按照显著性高低分别赋予不同的权重,完成不同运动方向特征的相互竞争。最后融合经过归一化处理的特征图以得到最终的运动显著图。该显著图中运动方向具有显著性的物体得到有效突出,达到了存在多个运动物体的情况时,运动方向上具有显著性的物体能够更加有效、智能地检测出来的目的。     

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.     

Joint striping noise removal and background clutter cancellation inIR naval surveillance systems

The clutter removal procedure for infrared (IR) naval surveillance systems presented is designed to manage a typical maritime scenario and is insensitive to the sharp transition between sea and sky across the horizon line. It is also effective for the removal of striping noise which arises as a consequence of the nonuniform calibration of the detector array. The low computational cost of this technique makes it well suited for real-time implementation. The effectiveness of the clutter removal procedure is illustrated on a set of experimental IR data     

Reconfigurable biologically inspired visual motion systems using modular neuromorphic VLSI chips

Visual motion information provides a variety of clues that enable biological organisms from insects to primates to efficiently navigate in unstructured environments. We present modular mixed-signal very large-scale integration (VLSI) implementations of the three most prominent biological models of visual motion detection. A novel feature of these designs is the use of spike integration circuitry to implement the necessary temporal filtering. We show how such modular VLSI building blocks make it possible to build highly powerful and flexible vision systems. These three biomimetic motion algorithms are fully characterized and compared in performance. The visual motion detection models are each implemented on separate VLSI chips, but utilize a common silicon retina chip to transmit changes in contrast, and thus four separate mixed-signal VLSI designs are described. Characterization results of these sensors show that each has a saturating response to contrast to moving stimuli, and that the direction of motion of a sinusoidal grating can be detected down to less than 5% contrast, and over more than an order of magnitude in velocity, while retaining modest power consumption.     

Organ motion detection in CT images using opposite rays in fan-beamprojection systems

Motion artifacts have been identified as a problem in medical tomography systems. While computed tomography (CT) imaging has been getting faster, there remains a need to detect and compensate for motions in clinical follow-up of neurological patients (multiple sclerosis, tumors, stroke, etc.), in cardiac imaging, and in any area in which failing to detect a motion artifact may lead to misdiagnosis. We have developed a novel algorithm to detect motion in brain images. The algorithm deals with detecting and isolating motion in the object domain using only the information available in the sinogram domain. The new "opposite ray algorithm" (ORA) addresses the issue of motion in the interior elements of the object. The ORA combines information from projections that are opposite in space and separated in time to isolate and identify the motion. A sinogram of motion is created, integrated and reconstructed to isolate the moving component. The algorithm can be used with conventional clinical scanners employing quarter-detector offset. The significant effect of quarter-detector offset on the ORA is investigated. The effects that a finite beamwidth and noise have on the ORA are also investigated. Both the similarity index and a correlation coefficient are used to evaluate the algorithm. The algorithm is successful when applied to cases exhibiting translational and translational-rotational motion. A similarity index of 0.88 is obtained in a typical case with both translational and rotational motion. Further development is recommended in the deformation case.     

A network of co-operative cameras for visual surveillance

A network of co-operative cameras for the visual surveillance of parking lots is presented. Such a network employs multiple subnets able to manage static and active cameras in a hierarchical framework. The system is able to track multiple targets simultaneously and in real-time throughout the controlled areas. The positions of detected objects, computed from different sensors, are fused considering a dynamic reliability factor for each sensor reading. Close-up recordings of suspicious events are obtained by tasking the active camera systems (ACSs). The co-operation is performed through a multicast communication system studied to transmit useful data both intra and inter networks. In particular, information about the position of the object to track, sent by a static camera system (SCS), is used by an ACS to operate an initial repositioning. The ACS compensates background changes owing to the camera motion, detects mobile objects in the scene and autonomously tracks the object of interest. Tracking results are presented in the context of a video surveillance application for a parking lot.     

Real-time video-shot detection for scene surveillance applications

A surveillance system with automatic video-shot detection and indexing capabilities is presented. The proposed system aims at detecting the presence of abandoned objects in a guarded environment and at automatically performing online semantic video segmentation in order to facilitate the human operator's task of retrieving the cause of an alarm. The former task is performed by operating image segmentation based on temporal rank-order filtering, followed by classification in order to reduce false alarms. The latter task is performed by operating temporal video segmentation when an alarm is detected. In the clips of interest, the key frame is the one depicting a person leaving a dangerous object, and is determined on the basis of a feature indicating the movement around the dangerous region. Experimental results are reported in terms of static region detection, classification, clip and key-frame detection errors versus different levels of complexity of the guarded environment, in order to establish the performance that can be expected from the system in different situations.     

红外警戒系统中的数据互联算法

文中研究了舰载红外警戒系统中的多目标数据互联算法，提出了二维广义扇形相关波站及门限参数的设置方法和红外多目标跟踪中的粗、精互联准则。，建立了航迹方位顺序号的概念，讨论了迷信息的存贮及顺序号的转换方式，定义了用于最近邻准则的统计距离，研究了航迹类型转换与互联质量设计问题。     

Self-organized night video enhancement for surveillance systems

Night video enhancement techniques are widely used for identifying suspicious activities captured by night visual surveillance systems. However, artificial light sources present in the surroundings deteriorate the visual quality of the video captured during night. This non-uniform illumination reduces the object identification and tracking capability of a real-time visual security system. Thus, a uniform enhancement technique is insufficient for handling such uneven illumination. In this paper, we propose a novel night video enhancement scheme based on a hierarchical self-organizing network. This proposed scheme automatically groups and enhances the neighboring pixels of dark and light regions in each frame. In this scheme, two-level self- organizing neural networks were hierarchically arranged to group similar pixels present in the night video frame. We applied the no-reference-based performance evaluation metrics for measuring the objective quality of the video. The experimental results showed that our proposed approach considerably enhances the visual perception of the video captured at night under varied illumination conditions.     

天基监视空间目标轨迹提取算法

序列星图中弱小目标的检测与定位是可见光天基监视中的关键技术之一,星图预处理的结果直接影响检测灵敏度及虚警率。文中引入一种在轨检测轨迹提取算法,该算法适用于高斯噪声的星图,由高斯最小二乘拟合、小区域滤波及星象边缘闽值分割三步组成。可抑制噪声背景减少虚假目标的同时,较好地保持星象边缘。通过算法性能分析可知,同美国天基可见关...     

Signal design for efficient detection in dispersive channels

Signal design for maximizing the efficiency of the Neyman-Pearson detection procedure in randomly dispersive media is investigated. The medium is modeled as a randomly time-varying linear filter; by viewing the filter transfer function as a homogeneous random field on the time-frequency plane, a second-order theory results that relates various second-order measures of the time and frequency structures of input and output processes. A signal design strategy is developed that dictates transmitting signals that produce output processes with degrees of freedom possessing a signal-to-noise ratio (SNR) in the vicinity of 2. A distribution of signal energy in the output time-frequency plane that achieves the proper SNR for each degree of freedom is deduced and is used to infer constraints on input ambiguity functions that maximize detection efficiency. The general structure of efficient input signals for both high and low SNR is briefly discussed.     

一种视频监控图像条纹噪声去除算法

针对视频图像中图像传感器故障引起的等间距横纹噪声去除问题。提出了基于陷波滤波器的去除条纹噪声算法;首先将视频条纹图进行傅里叶变换,通过频域累积分布函数映射法构造自适应滤波器,用该滤波器对变换后的条纹图像进行滤波,最后用Laplacian算子进行锐化处理得到最终去噪声图像。实验结果表明,本算法适合用于去除有图像传感器故障引起的等间距横纹噪声。