Adapting Stream Processing Framework for Video Analysis

AbstractStream processing (SP) became relevant mainly due to inexpensive and hence ubiquitous deployment of sensors in many domains (e.g., environmental monitoring, battle field monitoring). Other continuous data generators (surveillance, traffic data) have also prompted processing and analysis of these streams for applications such as traffic congestion/accidents and personalized marketing. Image processing has been researched for several decades. Recently there is emphasis on video stream analysis for situation monitoring due to the ubiquitous deployment of video cameras and unmanned aerial vehicles for security and other applications.This paper elaborates on the research and development issues that need to be addressed for extending the traditional stream processing framework for video analysis, especially for situation awareness. This entails extensions to: data model, operators and language for expressing complex situations, QoS (Quality of service) specifications and algorithms needed for their satisfaction. Specifically, this paper demonstrates inadequacy of current data representation (e.g., relation and arrable) and querying capabilities to infer long-term research and development issues

AN IP-BASED LIVE DATABASE APPROACH TO SURVEILLANCE APPLICATION DEVELOPMENT

With the proliferation of inexpensive cameras, video surveillance applications are becoming ubiquitous in many domains such as public safety and security, manufacturing, intelligent transportation systems, and healthcare. IP-based video surveillance technologies, in particular, are able to bring traditional video surveillance centers to virtually any computer at any location with an Internet connection. Today’s IP-based video surveillance systems, however, are designed for specific classes of applications. For instance, one cannot use a system designed for incident detection on highways to monitor patients in a healthcare facility. To support rapid development of video surveillance applications, we designed and implemented a new class of general purpose database management system, the live video database management system (LVDBMS). We view networked IP cameras as a special class of storage devices, and allow the user to formulate ad hoc queries expressed over live video feeds. These continuous queries are processed in real time using novel distributed computing techniques. With this environment, the users are able to develop various specific web-based video surveillance systems for a variety of applications. These systems can coexist in a unified LVDBMS framework to share the expensive deployment and operating costs of the camera networks. Our contribution is the introduction of a live database approach to video surveillance software development. In this paper, we describe our prototype and present the live video data model, the query language, and the query processing technique. 1

An Informatics-Based Approach To Object Tracking For Distributed Live Video Computing

Omnipresent camera networks have been a popular research topic in recent years. They are applicable to a range of monitoring tasks, from bridges to gas stations to the inside of industrial chemical tanks. Though a large body of existing work focuses on image and video processing techniques, very few address the usability of such systems or the implications of real-time video dissemination. In this article, we present our work on extending the LVDBMS prototype with a multifaceted object model to characterize objects in live video streams. This forms the basis for a cross-camera tracking framework which permits objects to be tracked from one video stream to another. With this infrastructure, real-time queries may be posed to monitor complex events that occur in multiple video streams simultaneously. This live video database environment provides a general-purpose platform for distributed live video computing with the goal of enabling rapid application development for camera networks. © 2012 Springer Science+Business Media, LLC

A General Framework For Managing And Processing Live Video Data With Privacy Protection

The sixteenth-century Florida borderlands provide a unique setting for evaluating gender and its meanings to colonizers of the Americas. Despite being explored by European conquistadors much earlier than other Western locales, the peninsula and its hinterlands generated few riches and served as the site for no substantial settlements until the late eighteenth century. This situation differed significantly from settlements in Mexico, Peru, New England, or Virginia, the centerpieces of most studies evaluating gender in the New World. Between 1527 and 1567, multiple Spanish and French expeditions to Florida produced ample documentation of European men\u27s distinct impressions of women, which aligned closely with their own ethnicities, and used these depictions to explain explorer successes and failures in the region. Conclusions reached in this evaluation of conquistador conceptualizations of women and gender in the Florida borderlands both validate existing paradigms and promote new perspectives regarding the Americas as a whole

Mobile Sensor Approach To Location-Based Services

Moving object database is the core technology for location-based services (LBS), permitting users to pose spatial queries about the environment around them. We introduce a sensor-based LBS approach that is more economical and scalable for large-scale deployments supporting a large user community. We discuss this framework in the context of k-nearest-neighbor queries. We present simulation results and efficiency analysis to show the effectiveness of the proposed technique. © 2010 IEEE

Processing Approximate Moving Range Queries In Mobile Sensor Environments

The ubiquity of mobile devices has led to a rising demand for location-based services and applications. A major part of these services is based on the location-detection capabilities of the mobile devices. Utilization of location data reported by the devices is associated with a certain amount of uncertainty due to the device\u27s mobility. In this paper, we examine an environment, which consists of mobile objects with no location-detection capabilities, and location-aware mobile sensors randomly scattered, that can sense the presence of mobile devices. These sensors can detect the identities of mobile objects that come within their sensing ranges but cannot infer their exact locations. The sensor readings are periodically reported to a database server. This system supports processing of mobile location-dependent range queries over mobile objects. The answer set of each query carries a certain degree of uncertainty due to the approximate nature of the reported object location data. We exploit scenarios of sensor range overlap to reduce the uncertainty inherent in the query result. Our work is validated through an extensive simulation study that provides assessment of the query results accuracy. © 2009 IEEE

An Informatics-Based Approach To Object Tracking For Distributed Live Video Computing

Omnipresent camera networks have been a popular research topic in recent years. Example applications include surveillance and monitoring of inaccessible areas such as train tunnels and bridges. Though a large body of existing work focuses on image and video processing techniques, very few address the usability of such systems or the implications of real-time video dissemination. In this paper, we present our work on extending the LVDBMS prototype with a multifaceted object model to better characterize objects in live video streams. This forms the basis for a cross camera tracking framework based on the informatics-based approach which permits objects to be tracked from one video stream to another. Queries may be defined that monitor the streams in real time for complex events. Such a new database management environment provides a general-purpose platform for distributed live video computing. © 2011 Springer-Verlag

A Novel Broadcast Technique For High-Density Ad Hoc Networks

Broadcasting in ad hoc networks is required for many routing and other network-layer protocols to request information like routes or locations about destination nodes. Most of these routing protocols use a simple flooding mechanism that can cause broadcast storms, particularly in high density environments. Although many techniques have been proposed to address the problem of broadcast storms, they require additional periodic location beacons or do not satisfactorily reduce transmission redundancy in high density environments. We propose Cell Broadcast, a broadcast protocol that significantly reduces redundancy without the use of beaconing and while maintaining complete reachability in a high density environment. The proposed technique divides a terrain into cells. These cells help a node to determine its geographic relationship with a broadcasting node. This geographic relationship can eliminate rebroadcasts not only from nodes close to a broadcasting node but also from a majority of nodes near the transmission edge of the broadcasting node. The effect is that, in a high density environment, only a few nodes located near the 4 diagonal corners of a transmission range need to rebroadcast to maintain 100% reachability. To the best of our knowledge, this technique is not present in any existing techniques that do not use location beaconing. Copyright 2006 ACM