Distributed intelligence for multi-camera visual surveillance

Latest advances in hardware technology and state of the art of computer vision and artificial intelligence research can be employed to develop autonomous and distributed monitoring systems. The paper proposes a multi-agent architecture for the understanding of scene dynamics merging the information streamed by multiple cameras. A typical application would be the monitoring of a secure site, or any visual surveillance application deploying a network of cameras. Modular software (the agents) within such architecture controls the different components of the system and incrementally builds a model of the scene by merging the information gathered over extended periods of time. The role of distributed artificial intelligence composed of separate and autonomous modules is justified by the need for scalable designs capable of co-operating to infer an optimal interpretation of the scene. Decentralizing intelligence means creating more robust and reliable sources of interpretation, but also allows easy maintenance and updating of the system. Results are presented to support the choice of a distributed architecture, and to prove that scene interpretation can be incrementally and efficiently built by modular software.     

Adaptive online camera coordination for multi-camera multi-target surveillance

Online camera selection is introduced as a result of the improved mobility of cameras and the increased scale of surveillance systems. Most existing camera assignment algorithms achieve an optimal observation under the assumption of the unlimited camera computational capacities. However, practical surveillance systems experience resource limitation and see a degradation in the system performance as the number of objects to be processed increases. To address this issue, we propose an adaptive camera assignment algorithm considering the limited camera computational capacities. In so doing, camera resources can be dynamically allocated to multiple objects according to their priorities and the current camera computational load. Experimental results illustrate that the proposed camera assignment algorithm is capable of maintaining a constant frame rate and achieving a substantially decreased object rejection rate in comparison with the algorithm presented by Bakhtari and Benhabib.     

Coopetitive multi-camera surveillance using model predictive control

We present a generic framework for enhanced active multi-sensing. We propose a coopetitive interaction approach, which combines the salient features of cooperation and competition with an aim to optimize the cooperation among sensors to achieve best results at the system level rather than redundantly implementing cooperation at each stage. We also employ model predictive control based forward state estimation method for counter-acting various delays faced in multi-sensor environments. The results obtained for two different visual surveillance adaptations with different number of cameras and different surveillance goals provide clear evidence for the improvements created by adoption of the proposed enhancements.     

CrossbowCam: a handheld adjustable multi-camera system

Multimedia Tools and Applications - This paper presents a novel multi-functional, low-cost handheld multi-camera system (one dimensional camera array) - “CrossbowCam”. The CrossbowCam...     

Performance analysis for automated gait extraction and recognition in multi-camera surveillance

Many studies have confirmed that gait analysis can be used as a new biometrics. In this research, gait analysis is deployed for people identification in multi-camera surveillance scenarios. We present a new method for viewpoint independent markerless gait analysis that does not require camera calibration and works with a wide range of walking directions. These properties make the proposed method particularly suitable for gait identification in real surveillance scenarios where people and their behaviour need to be tracked across a set of cameras. Tests on 300 synthetic and real video sequences, with subjects walking freely along different walking directions, have been performed. Since the choice of the cameras’ characteristics is a key-point for the development of a smart surveillance system, the performance of the proposed approach is measured with respect to different video properties: spatial resolution, frame-rate, data compression and image quality. The obtained results show that markerless gait analysis can be achieved without any knowledge of camera’s position and subject’s pose. The extracted gait parameters allow recognition of people walking from different views with a mean recognition rate of 92.2% and confirm that gait can be effectively used for subjects’ identification in a multi-camera surveillance scenario.     

关系数据库层次树查询机制浅析

大多数关系数据库应用系统的结构体系和查询要求都呈现很强的层次特征.在进行数据库查询过程中,用一般的查询机制来查询具有层次结构的数据是较为繁琐的.目前Oracle 9i及以上版本和SQL Server 2005都引入了层次树查询机制,层次树查询是一种针对关系数据库中层次结构数据查询的树型解决方案,可较好地解决此类复杂的层次查询问题.以Oracle 9i数据库为例,结合某公司的部门组织结构,对层次树查询机制进行了实例分析与研究.     

Efficient multi-camera vehicle detection,tracking, and identification in a tunnel surveillance application

This paper presents an integrated solution for the problem of detecting, tracking and identifying vehicles in a tunnel surveillance application, taking into account practical constraints including real-time operation, poor imaging conditions, and a decentralized architecture. Vehicles are followed through the tunnel by a network of non-overlapping cameras. They are detected and tracked in each camera and then identified, i.e. matched to any of the vehicles detected in the previous camera (s). To limit the computational load, we propose to reuse the same set of Haar-features for each of these steps. For the detection, we use an AdaBoost cascade. Here we introduce a composite confidence score, integrating information from all stages of the cascade. A subset of the features used for detection is then selected, optimizing for the identification problem. This results in a compact binary ‘vehicle fingerprint’, requiring minimal bandwidth.Finally, we show that the same subset of features can also be used effectively for tracking. This Haar-features based ‘tracking-by-identification’ yields surprisingly good results on standard datasets, without the need to update the model online. The general multi-camera framework is validated using three tunnel surveillance videos.     

A multi-camera vision system for fall detection and alarm generation

Abstract: In-house video surveillance can represent an excellent support for people with some difficulties (e.g. elderly or disabled people) living alone and with a limited autonomy. New hardware technologies and in particular digital cameras are now affordable and they have recently gained credit as tools for (semi-)automatically assuring people's safety. In this paper a multi-camera vision system for detecting and tracking people and recognizing dangerous behaviours and events such as a fall is presented. In such a situation a suitable alarm can be sent, e.g. by means of an SMS. A novel technique of warping people's silhouette is proposed to exchange visual information between partially overlapped cameras whenever a camera handover occurs. Finally, a multi-client and multi-threaded transcoding video server delivers live video streams to operators/remote users in order to check the validity of a received alarm. Semantic and event-based transcoding algorithms are used to optimize the bandwidth usage. A two-room setup has been created in our laboratory to test the performance of the overall system and some of the results obtained are reported.     

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.     

Hierarchical to relational database migration

Although database migration has not yet been extensively researched, three predominant software solutions have evolved: language interfaces, source-code conversion, and data propagation. The authors consider how Swiss Bank and IBM designed and developed the IBM Data Propagator MVS/ESA, which supports interactive and batch data propagation. This software migrates data from the hierarchical IMS to the relational DB2, without affecting existing applications. It supports forward and reverse data propagation, which lets heterogeneous databases coexist. At Swiss Bank, the Data Propagator MVS/ESA handles the main customer and account databases at all five computer centers in Switzerland     

A multi-camera image processing and visualization system for train safety assessment

In this paper we present a machine vision system to efficiently monitor, analyse and present visual data acquired from a railway overhead gantry equipped with multiple cameras. This solution aims to improve the safety of daily life railway transportation in a two-fold manner: (1) by estimating multiple safety requirements using image analysis algorithms that can process large imagery of trains (2) by helping train safety operators to detect any possible malfunction on a train. The system exploits high-rate visible and thermal cameras that observe a train passing under a railway overhead gantry. The machine vision system is composed of three principal modules: (1) an automatic wagon identification system, recognizing the wagon ID according to the UIC classification of railway coaches; (2) a system for the detection and localization of the pantograph of the train; (3) a temperature monitoring system. These three machine vision modules process batch trains sequences and their resulting analysis are presented to an operator using a multitouch user interface.     

多摄像机目标跟踪系统综述

介绍国内外对多摄像机的研究现状;描述了多摄像机目标跟踪系统的各种构架并进行分析比较;详细阐述各功能模块,分别就算法研究现状、存在的问题及发展趋势进行了分析和总结;最后对研究前景进行展望.     

A semi-supervised system for players detection and tracking in multi-camera soccer videos

This paper presents a complete, general and modular system which after a simple previous configuration is able to detect and track each player on the court or field. The presented multi-camera system is based on a mono-camera object detection and tracking system originally designed for video surveillance applications. Target sports of the developed system are team sports (e.g., basketball, soccer). The main objective of this paper is to present a semi-supervised system able to detect and track the players in multi-camera sports videos, focusing on the fusion of different tracks of detected blobs in order to match tracks across cameras. The proposed system is simpler than other systems from the state of the art, can operate in real time and has margin to be improved and to reduce supervision adding additional complexity. In addition to the detection and tracking system, an evaluation system has been designed to obtain quantitative results of the system performance.     

On designing a database management system for a computer-aided engineering software system

The renaissance of engineering design can be attributed to the phenomenal growth in the microprocessor industry. The basic difference between the new and the traditional approach is one of outlook. Complex design situations involve multidisciplines. However this has made the task of integrating and transferring design information among these disciplines very difficult. Database management systems (DBMS) provide attractive solutions to these problems. A centralized control of data ensures that redundancy can be reduced, inconsistency can be avoided, data can be shared, standards can be enforced, and conflicting requirements can be handled. This paper takes the reader through the steps required to configure an engineering DBMS. The different data models are explained and their usage in CAD/CAM settings is illustrated. The importance of data independence, modularity, efficiency, and protability is emphasized.     

Development and characterization of a multi-camera 2D-vision system for enhanced performance of a drink serving robotic cell

A 2D-vision system is integrated into a drink-serving robotic cell, to enhance its flexibility. Two videocameras are used in a hybrid configuration scheme. The former is rigidly mounted on the robot end effector, the latter is fixed to the workplace. The robot cell is based on two Denso robots that interoperate to simulate real human tasks. Blob analysis, template matching and edge detection algorithms cooperate with motion procedures for fast object recognition and flexible adaptation to the environment. The paper details the system workflow, with particular emphasis to the vision procedures. The experimental results show their performance in terms of flexibility and robustness against defocusing, lighting conditions and noise.