基于USB摄像头的嵌入式远程视频监控系统

介绍一种用USB摄像头作为采集终端的视频监控系统,用户在远程端可以监控USB摄像头获取实时视频,并能够控制云台进行转动。整个系统能够独立完成实时视频的采集、处理及传输功能,可广泛应用在远程监控系统、可视电话、工业控制等领域。

集控站智能网络视频监控系统

集控站智能网络视频监控系统充分利用了集控站现有资源,在保障集控站数据采集功能安全运行的前提下,实现对集控站的远程视频采集。使用集控站现有通信网络,将所有通信格式都统一到以IP方式,实现对集控站和厂站设备的监控。

办公楼视频监控系统设计与实现

现代市场经济快速发展促进爹我国功能专业化的高层办公楼宇的建设。但是由于现代办公楼宇内企业较多、人员流动性大，消防、安全隐患也随之增大。针对这样的情况，我国新建办公楼宇多采用安装视频、监控系统来增加安全．监控力度，提高监控效率。文中就办公楼视频监控系统的设计与实现进行了简要论述。

浅析双绞线视频传输技术在琳桥闸监控的应用

阐述将双绞线视频传输技术应用到闸站视频监控,分析双绞线传输技术的原理和特点;结合琳桥闸现场情况,设计实施方案并进行施工实现。通过对项目实施效果开展分析总结,得出双绞线视频传输技术在视频监控中是可行的,具有推广的价值。

齐齐哈尔城市安防监控系统设计方案

提出一种适于齐齐哈尔发展的城市安防监控系统。

百度EasyDL人工智能技术助力高校控烟应用研究

文章对目前我国大学生校园吸烟较为严重的现象进行了阐述,报告了视频监控技术、红外热成像技术以及烟雾报警技术等几种常见校园控烟方法存在的弊端。针对传统控烟技术的缺陷提出了一种基于人工智能技术应用的校园监控学生吸烟解决方案,前期对吸烟者与未吸烟者大量图片的采集,训练并构建出精准度较高的监测模型以达到自动识别吸烟者的目的,通过多次验证达到了预期的控烟效果。

Video-based urban expressway traffic measurement and performance monitoring

This paper presents an urban expressway video surveillance and monitoring system for traffic flow measurement and abnormal performance detection. The proposed flow detection module collects traffic flow statistics in real time by leveraging multi-vehicle tracking information. Based on these online statistics, road operating situations can be easily obtained. Using spatiotemporal trajectories, vehicle motion paths are encoded by hidden Markov models. With path division and parameter matching, abnormal performances containing extra low or high speed driving, illegal stopping and turning are detected in real scenes. The traffic surveillance approach is implemented and evaluated on a DM642 DSP-based embedded platform. Experimental results demonstrate that the proposed system is feasible for the detection of vehicle speed, vehicle counts and road efficiency, and it is effective for the monitoring of the aforementioned anomalies with low computational costs.

“药物使用剂量和频次智能化监控系统”用于非抗菌药物监控的实施及效果分析

目的:借助"药物使用剂量和频次智能化监控系统"促进非抗菌药物合理使用。方法:基于医院信息系统,通过"药物使用剂量和频次智能化监控系统"实现非抗菌药物使用剂量和频次与患者年龄、体质量、体表面积、肾功能状况等信息相链接,并随机抽取我院1天的住院患者非抗菌药物处方(1315张)进行审查。结果:对无需按年龄、肾功能等调整剂量和频次的药物,系统审查出单次剂量过大而频次适中警示200条,单次剂量过大而频次不足警示91条,单次剂量适中而频次不足警示43条,单次剂量适中而频次过多警示41条,单次剂量过小和频次适中或不足警示15条。而对需按年龄、肾功能等调整剂量和频次的药物,系统审查出剂量过大和(或)频次过多警示11条。结论:这种链接方式切实可行,当非抗菌药物处方中出现不符合说明书规定的使用剂量和(或)频次时,能够被该系统识别,而其实用价值有待实践检验。

基于HFC接入网的几种应用系统

本文简要介绍了HFC接入网双向传输平台的实现方案 ,着重对基于HFC双向传输平台的会议电视、射频监控、多媒体教学三种应用系统的工作原理进行了描述。

A new approach for real time object detection and tracking on high resolution and multi-camera surveillance videos using GPU

High resolution cameras and multi camera systems are being used in areas of video surveillance like security of public places, traffic monitoring, and military and satellite imaging. This leads to a demand for computational algorithms for real time processing of high resolution videos. Motion detection and background separation play a vital role in capturing the object of interest in surveillance videos, but as we move towards high resolution cameras, the time-complexity of the algorithm increases and thus fails to be a part of real time systems. Parallel architecture provides a surpass platform to work efficiently with complex algorithmic solutions. In this work, a method was proposed for identifying the moving objects perfectly in the videos using adaptive background making, motion detection and object estimation. The pre-processing part includes an adaptive block background making model and a dynamically adaptive thresholding technique to estimate the moving objects. The post processing includes a competent parallel connected component labelling algorithm to estimate perfectly the objects of interest. New parallel processing strategies are developed on each stage of the algorithm to reduce the time-complexity of the system. This algorithm has achieved a average speedup of 12.26 times for lower resolution video frames(320×240, 720×480, 1024×768) and 7.30 times for higher resolution video frames(1360×768, 1920×1080, 2560×1440) on GPU, which is superior to CPU processing. Also, this algorithm was tested by changing the number of threads in a thread block and the minimum execution time has been achieved for 16×16 thread block. And this algorithm was tested on a night sequence where the amount of light in the scene is very less and still the algorithm has given a significant speedup and accuracy in determining the object.

Design of Environmental Monitoring and Control System for Large-scale Pig House with Fermentation Bed

The design and assembly of environmental monitoring and control system for large-scale pig house with fermentation bed helped to solve the problem of environmental automatic control in piggery.The sensors would monitor the temperature,humidity,light,wind direction,wind speed,CO2,NH3and other parameters.On-line real-time data collection was achieved.The expert system was constructed to control the temperature in piggery below 30℃,to control the air and mattress humidities higher than 65%.Under the conditions of different season or different wind speed,even in day and night,the control actuators were different.The actuators included fanning wet curtain,lighting,micro spraying,spraying,propeller fan,electric aluminum alloy shutter and spraying systems on the roof.The actuators were integrated,and they control the piggery environment simultaneously.The system also designed the remote video monitor interface,parameter-monitoring curved interface and operation interface,which provided a good man-machine interface.

A Nonparametric Approach to Foreground Detection in Dynamic Backgrounds

Foreground detection is a fundamental step in visual surveillance.However,accurate foreground detection is still a challenging task especially in dynamic backgrounds.In this paper,we present a nonparametric approach to foreground detection in dynamic backgrounds.It uses a history of recently pixel values to estimate background model.Besides,the adaptive threshold and spatial coherence are introduced to enhance robustness against false detections.Experimental results indicate that our approach achieves better performance in dynamic backgrounds compared with several approaches.

Research on the measurement of belt speed by video in coal mine based on improved template matching algorithm

In order to improve the intelligence of video monitoring system of belt and make up the deficiency of higher failure rate and bad real-time performance in the traditional systems of measurement of belt speed, according to the fact that the light of coal mine is uneven, the strength of light changes greatly, the direction of belt movement is constant, and the position of camera was fixed, various algorithms of speed measurement by video were studied, and algorithm for template matching based on sum of absolute differences （SAD） and correlation coefficient was proposed and improved, besides, the tracking of feature regions was realized. Then, a camera calibration method using the invariance of the cross-ratio was adopted and the real-time measurement of belt speed by the hardware platform based on DM642 was realized. Finally, experiment results show that this method not only has advantages of high precision and strong anti-jamming capability but also can real-time reflect the changes of belt speed, so it has a comprehensive applicability.

UTILITY OPTIMIZATION SCHEDULING FOR MULTI-POINT VIDEO SURVEILLANCE IN UBIQUITOUS NETWORK

Resource allocation is an important problem in ubiquitous network. Most of the existing resource allocation methods considering only wireless networks are not suitable for the ubiquitous network environment, and they will harm the interest of individual users with instable resource requirements. This paper considers the multi-point video surveillance scenarios in a complex network environment with both wired and wireless networks. We introduce the utility estimated by the total costs of an individual network user. The problem is studied through mathematical modeling and we propose an improved problem-specific branch-and-cut algorithm to solve it. The algorithm follows the divide-and-conquer principle and fully considers the duality feature of network selection. The experiment is conducted by simulation through C and Lingo. And it shows that compared with a centralized random allocation scheme and a cost greed allocation scheme, the proposed scheme has better per- formance of reducing the total costs by 13.0% and 30.6% respectively for the user.

Background modeling methods in video analysis： A review and comparative evaluation

Foreground detection methods can be applied to efficiently distinguish foreground objects including moving or static objects from back- ground which is very important in the application of video analysis, especially video surveillance. An excellent background model can obtain a good foreground detection results. A lot of background modeling methods had been proposed, but few comprehensive evaluations of them are available. These methods suffer from various challenges such as illumination changes and dynamic background. This paper first analyzed advantages and disadvantages of various background modeling methods in video analysis applications and then compared their performance in terms of quality and the computational cost. The Change detection.Net （CDnet2014） dataset and another video dataset with different envi- ronmental conditions （indoor, outdoor, snow） were used to test each method. The experimental results sufficiently demonstrated the strengths and drawbacks of traditional and recently proposed state-of-the-art background modeling methods. This work is helpful for both researchers and engineering practitioners. Codes of background modeling methods evaluated in this paper are available atwww.yongxu.org/lunwen.html.

Video segmentation using Maximum Entropy Model

Detecting objects of interest from a video sequence is a fundamental and critical task in automated visual surveillance. Most current approaches only focus on discriminating moving objects by background subtraction whether or not the objects of interest can be moving or stationary. In this paper, we propose layers segmentation to detect both moving and stationary target objects from surveillance video. We extend the Maximum Entropy (ME) statistical model to segment layers with features, which are collected by constructing a codebook with a set of codewords for each pixel. We also indicate how the training models are used for the discrimination of target objects in surveillance video. Our experimental results are presented in terms of the success rate and the segmenting precision.

Robust background subtraction in traffic video sequence

For intelligent transportation surveillance, a novel background model based on Mart wavelet kernel and a background subtraction technique based on binary discrete wavelet transforms were introduced. The background model kept a sample of intensity values for each pixel in the image and used this sample to estimate the probability density function of the pixel intensity. The density function was estimated using a new Marr wavelet kernel density estimation technique. Since this approach was quite general, the model could approximate any distribution for the pixel intensity without any assumptions about the underlying distribution shape. The background and current frame were transformed in the binary discrete wavelet domain, and background subtraction was performed in each sub-band. After obtaining the foreground, shadow was eliminated by an edge detection method. Experimental results show that the proposed method produces good results with much lower computational complexity and effectively extracts the moving objects with accuracy ratio higher than 90%, indicating that the proposed method is an effective algorithm for intelligent transportation system.

Motion cue based pedestrian detection with two-frame-filtering

This study proposes a motion cue based pedestrian detection method with two-trame-filtering （Tff） for video surveillance. The novel motion cue is exploited by the gray value variation between two frames. Then Tff processing filters the gradient magnitude image by the variation map. Summa- tions of the Tff gradient magnitudes in cells are applied to train a pre-deteetor to exclude most of the background regions. Histogram of Tff oriented gradient （HTffOG） feature is proposed for pedestrian detection. Experimental results show that this method is effective and suitable for real-time surveil- lance applications.

Abnormal activity detection for surveillance video synopsis

Video synopsis is an effective and innovative way to produce short video abstraction for huge video archives,while keeping the dynamic characteristic of activities in the original video.Abnormal activity,as the critical event,is always the main concern in video surveillance context.However,in traditional video synopsis,all the normal and abnormal activities are condensed together equally,which can make the synopsis video confused and worthless.In addition,the traditional video synopsis methods always neglect redundancy in the content domain.To solve the above-mentioned issues,a novel video synopsis method is proposed based on abnormal activity detection and key observation selection.In the proposed algorithm,activities are classified into normal and abnormal ones based on the sparse reconstruction cost from an atomically learned activity dictionary.And key observation selection using the minimum description length principle is conducted for eliminating content redundancy in normal activity.Experiments conducted in publicly available datasets demonstrate that the proposed approach can effectively generate satisfying synopsis videos.

A real-time 5/3 lifting wavelet HD-video de-noising system based on FPGA

In accordance with the application requirements of high definition(HD) video surveillance systems,a real-time 5/3 lifting wavelet HD-video de-noising system is proposed with frame rate conversion(FRC) based on a field-programmable gate array(FPGA),which uses a 3-level pipeline paralleled 5/3 lifting wavelet transformation and reconstruction structure,as well as a fast BayesS hrink adaptive threshold filtering module.The proposed system demonstrates de-noising performance,while also balancing system resources and achieving real-time processing.The experiments show that the proposed system's maximum operating frequency(through logic synthesis and layout using Quartus 13.1 software) can reach 178 MHz,based on the Altera Company's Stratix III EP3SE80 series FPGA.The proposed system can also satisfy real-time de-noising requirements of 1920 × 1080 at60 fps HD-video sources,while also significantly improving the peak signal to noise rate of the denoising images.Compared with similar systems,the system has the advantages of high operating frequency,and the ability to support multiple source formats for real-time processing.