This paper presents a novel method for video-based traffic state detection on motorways performed on smart cameras. Camera calibration parameters are obtained from the known length of lane markings. Mean traffic speed is estimated from Kanade-Lucas-Tomasi (KLT) optical flow method using a robust outlier detection. Traffic density is estimated using a robust statistical counting method. Our method has been implemented on an embedded smart camera and evaluated under different road and illumination conditions. It achieves a detection rate of more than 95% for stationary traffic.

This paper presents a new method for estimating the level of service (LOS) on motorways in the compressed video domain. The method performs statistical computations on motion vectors of MPEG4 encoded video streams within a predefined region of interest to determine a set of four motion features describing the speed and density of the traffic stream. These features are fed into a Gaussian radial basis function network to classify the corresponding LOS. To improve the classification results, vectors of moving objects are clustered and outliers are eliminated. The proposed method is designed to be executed on a server system, where a large number of camera live streams can be analyzed in parallel in real-time. Evaluations with a comprehensive set of real-world training and test data from an Austrian motorway have shown an average accuracy of 86.7% on the test data set for classifying all four LOS levels. With a mean execution time of 48 microseconds per frame on a common server, hundreds of video streams can be analyzed in real-time.

Summary form only given. Automated code analysis is technology aimed at locating, describing and repairing areas of weakness in code. Code weaknesses range from security vulnerabilities, logic errors, concurrency violations, to improper resource usage, violations of architectures or coding guidelines. Common to all code analysis techniques is that they build abstractions of code and then check those abstractions for properties of interest. For instance a type checker computes how types are used, abstract interpreters and symbolic evaluators check how values flow, model checkers analyze how state evolves. Building modern program analysis tools thus requires a multi-pronged approach to find a variety of weaknesses. In this talk I will discuss and compare several program analysis tools, which MSR build during the last ten years. They include theorem provers, program verifiers, bug finders, malware scanners, and test case generators. I will describe the need for their development, their innovation, and application. Many of these tools had considerable impact on Microsoft's development practices, as well as on the research community. Some of them are being shipped in products such as the Static Driver Verifier or as part of Visual Studio. Performing program analysis as part of quality assurance is meanwhile standard practice in many software development companies. However several challenges have not yet been resolved. Thus, I will conclude with a set of open challenges in program analysis which hopefully triggers new aspiring directions in our joint quest of delivering predictable software that is free from defect and vulnerabilities.

Universal plug and play (UPnP) is a widely accepted standard for automatically detecting devices and services in a local area network as well as for describing and controlling them. In order to deal with multimedia devices and especially content, in 2002 the UPnP-AV standard definition was released. It defines device and service descriptions for media servers and renderers. Thereby, the media server's content directory service allows an easy management and the exchange of metadata about the provided media data. Media content became browsable by semantic meta information about it. There are still two major drawbacks of UPnP-AV, which make its usage in real world multimedia communication scenarios very difficult. First, searching for similar content on distributed media servers with a huge number of media files is not economically possible. Second, the media content must be consumed by Renderers as provided by the Servers, independently of their terminal capabilities and network connections. In order to deal with these two drawbacks, this work proposes a novel approach of metadata integration and media transcoding in UPnP networks. First, the Media Server is extended by a control point which offers discovery of other media servers and fetches metadata from their content directories. Furthermore, it integrates the gathered information in its own content directory. Control Points are then able to query this Integrating Media Server for a desired content, and get a network-complete search result. Second, terminal and network capabilities of the Renderers are taken into account in order to transcode and transmit the content in a suitable way for the consuming device. These two approaches of metadata integration and media data adaptation enable searchable logical views on tailored multimedia content in UPnP-AV networks.