M2Tracker: A Multi-View Approach to Segmenting and Tracking People in a Cluttered Scene

When occlusion is minimal, a single camera is generally sufficient to detect and track objects. However, when the density of objects is high, the resulting occlusion and lack of visibility suggests the use of multiple cameras and collaboration between them so that an object is detected using information available from all the cameras in the scene.In this paper, we present a system that is capable of segmenting, detecting and tracking multiple people in a cluttered scene using multiple synchronized surveillance cameras located far from each other. The system is fully automatic, and takes decisions about object detection and tracking using evidence collected from many pairs of cameras. Innovations that help us tackle the problem include a region-based stereo algorithm capable of finding 3D points inside an object knowing only the projections of the object (as a whole) in two views, a segmentation algorithm using bayesian classification and the use of occlusion analysis to combine evidence from different camera pairs.The system has been tested using different densities of people in the scene. This helps us determine the number of cameras required for a particular density of people. Experiments have also been conducted to verify and quantify the efficacy of the occlusion analysis scheme.     

Semi-supervised vision-based maritime surveillance system using fused visual attention maps

This paper presents a vision-based system for maritime surveillance, using moving PTZ cameras. The proposed methodology fuses a visual attention method that exploits low-level image features appropriately selected for maritime environment, with appropriate tracker, without making any assumptions about environmental or visual conditions. The offline initialization is based on large graph semi-supervised technique. System’s performance was evaluated with videos from cameras placed at Limassol port and Venetian port of Chania. Results suggest high detection ability, despite dynamically changing visual conditions and different kinds of vessels, all in real time.     

Direct range measurement by linear stereovision for real-time obstacle detection in road traffic

This paper describes an obstacle detection method based on a passive 3D sensor using two line-scan cameras instead of standard video cameras. This approach permits good precision as well as low computational requirements, which allows a real-time implementation on a small, low cost computer, as required for obstacle detection on a car. Real-world examples are presented, that show the efficiency of the system.     

基于多传感器的智能车系统设计

主要介绍电磁、光电、CMOS摄像头和测速传感器在智能车控制系统中的应用.以MC9S12XS128单片机作为系统的控制核心,设计了能够自主循迹的智能车,着重叙述信号检测模块.信号检测包括路径和反馈速度检测,分别使用了电磁、光电、CMOS摄像头和编码器等传感器,并运用PID算法计算PWM对电机和舵机的控制.实际测试表明,智...     

Toward a sentient environment: real-time wide area multiple human tracking with identities

In this paper, we presented a fully integratedreal-time computer vision system that can detect and track multiple humans in a wide-area using a network of stereo cameras. Continuous human identities are achieved by fusing video tracking with different kinds of biometric devices. The system also provides immersive visualization which enables the users to conveniently navigate through space and time and query useful events. The key innovations include stereo-based multi-object detection and tracking, a unified approach for fusing multiple sensors of different modalities, visualization and user interface design.     

Real-time multi-camera video analytics system on GPU

In this article, parallel implementation of a real-time intelligent video surveillance system on Graphics Processing Unit (GPU) is described. The system is based on background subtraction and composed of motion detection, camera sabotage detection (moved camera, out-of-focus camera and covered camera detection), abandoned object detection, and object-tracking algorithms. As the algorithms have different characteristics, their GPU implementations have different speed-up rates. Test results show that when all the algorithms run concurrently, parallelization in GPU makes the system up to 21.88 times faster than the central processing unit counterpart, enabling real-time analysis of higher number of cameras.     

基于网络摄像机的入侵监视系统的设计

利用网络摄像机和个人电脑，提出了1种低廉的方法来实现入侵监测系统（IDS），使入侵监测系统不仅具备基本的监视、录像、回放和入侵监测等功能，由于该系统使用因特网，从而克服设备间的距离限制；另外，由于网络摄像机使用TCP／IP协议组，使该系统的安装费用也比CCTV或DVR大大减少。     

Video fire detection – Review

This is a review article describing the recent developments in Video based Fire Detection (VFD). Video surveillance cameras and computer vision methods are widely used in many security applications. It is also possible to use security cameras and special purpose infrared surveillance cameras for fire detection. This requires intelligent video processing techniques for detection and analysis of uncontrolled fire behavior. VFD may help reduce the detection time compared to the currently available sensors in both indoors and outdoors because cameras can monitor “volumes” and do not have transport delay that the traditional “point” sensors suffer from. It is possible to cover an area of 100 km² using a single pan-tilt-zoom camera placed on a hilltop for wildfire detection. Another benefit of the VFD systems is that they can provide crucial information about the size and growth of the fire, direction of smoke propagation.     

一种基于特征匹配的目标入侵检测方法

视频监控中常用云台摄像机监控视场较大的区域.对于云台摄像机跟随拍摄的情况,提出了一种基于特征匹配的目标入侵检测方法.通过提取的尺度不变特征变换(SIFT)特征点对,将当前图像和全景图像进行匹配,从而得到当前图像和全景图像投影关系,再将当前图像的坐标系变换到全景图像下,最后运用差分法,找到入侵目标.实验结果表明,即使当前图像与全景图像存在尺度、缩放、形变等差异,通过本方法也可正确地检测出入侵目标.     

基于立体视觉运动速度检测系统的研究及实现

介绍了一种基于立体视觉的运动速度检测系统的结构框架。系统在采集卡自带的软件开发包的基础上进行二次软件开发,加入了摄像机标定和图像处理分析部分。整个检测系统主要包括图像采集和运动检测两大环节;涵盖摄像机标定、图像获取及预处理、目标分割、3D定位、速度求取5个功能模块,并具有友好的操作界面,方便用户使用。文章重点针对目标分割和定位中所采用的技术方法展开了讨论。该系统可以具体应用在车辆和游乐设施等的运动速度检测上,在设备的安全运行以及交通监管方面有重要意义。