A growing number of mobile users prefer to access information and even make critical business decisions using their mobile phones. We present an integrated architecture developed at SAP Research as a platform for mobile business applications. The immediate goal is to allow mobile users to access information and services provided by the business back-end servers. The long-term goal is to develop techniques to overcome many problems mobile users face under such constraints as limited bandwidth, computational power and storage resources. The framework that we propose in this paper enables business applications connected to SAP through common mobile devices. SAP users can access business data and applications on the back- end server and execute tasks without a PC. We present components of the Lightweight Architecture (LWA) with specific components in the areas of data management, data compression, connectivity, and user interfaces.

This paper provides a brief description of a research project on using Ajax to enhance mobile Web applications for enterprise use. The project, known as MobileWeaver Ajax Framework, leverages enterprise SOA (Service Oriented Architecture) and the latest web technologies on mobile devices.

The amount of digital multimedia content available to consumers is growing due to the digital capturing devices such as digital cameras and camcorders. With this increase in content, it becomes important for people to be able to browse and search for content in a timely manner. To enable efficient content-based video browsing, extracted descriptions and annotations are needed to represent the content. We present algorithms for the automatic extraction of highlights in video using audio, text and visual features. These extracted descriptions can be used for selective browsing of sports videos. We also present the experimental results for the proposed algorithms on several hours of sports programs.

With the rapid proliferation of multimedia applications that require video data management, it is becoming more desirable to provide proper video data indexing techniques capable of representing the rich semantics in video data. In real-time applications, the need for efficient query processing is another reason for the use of such techniques. We present models that use the object motion information in order to characterize the events to allow subsequent retrieval. Algorithms for different spatiotemporal search cases in terms of spatial and temporal translation and scale invariance have been developed using various signal and image processing techniques. We have developed a prototype video search engine, PICTURESQUE (pictorial information and content transformation unified retrieval engine for spatiotemporal queries) to verify the proposed methods. Development of such technology will enable true multimedia search engines that will enable indexing and searching of the digital video data based on its true content.

Article Indexing and retrieval of video based on spatial relation sequences Share on Authors: Serhan Dağtaş Philips Research - USA 345, Scarborough Road, Briarcliff Manor, NY Philips Research - USA 345, Scarborough Road, Briarcliff Manor, NYView Profile , Arif Ghafoor School of Electrical and Computer Eng., Purdue University, West Lafayette, IN School of Electrical and Computer Eng., Purdue University, West Lafayette, INView Profile Authors Info & Claims MULTIMEDIA '99: Proceedings of the seventh ACM international conference on Multimedia (Part 2)October 1999 Pages 119–122https://doi.org/10.1145/319878.319910Online:01 October 1999Publication History 4citation388DownloadsMetricsTotal Citations4Total Downloads388Last 12 Months1Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access

We propose a graphical data model for specifying spatio-temporal semantics of video data. The proposed model segments a video clip into subsegments consisting of objects. Each object is detected and recognized, and the relevant information of each object is recorded. The motions of objects are modeled through their relative spatial relationships as time evolves. Based on the semantics provided by this model, a user can create his/her own, object-oriented view of the video database. Using the propositional logic, we describe a methodology for specifying conceptual queries involving spatio-temporal semantics and expressing views for retrieving various video clips. Alternatively, a user can sketch the query, by exemplifying the concept. The proposed methodology can be used to specify spatio-temporal concepts at various levels of information granularity.>