1259464
Using Temporal Semantics for Live Media Stream Queries
Querying live media streams is a challenging problem that becomes an essential requirement in a growing number of applications. We address the problem of evaluating continuous queries on media streams produced by media sources such as webcams and microphones. The temporal attributes and the order of stream tuples play essential roles in live stream generation and query execution. Furthermore, the temporal constraints and query semantics of related streams provide additional query optimization opportunities. We investigate the modeling issues and introduce the query processing techniques of a live media stream management system (MedSMan), including media capturing, automatic feature generating, declaration and query languages, temporal stream operators and querying algorithms. A prototype is implemented and we present experimental results to show the performance of our prototype using various real-time media experiments.
9521877
Using stream semantics for continuous queries in media stream processors
In the case of media and feature streams, explicit inter-stream constraints exist and can be exploited in the evaluation of continuous queries in the spirit of semantic query optimization. We express these properties using a media stream declaration language MSDL. In the demonstration, we present IMMERSI-MEET, an application built around an immersive environment. The IMMERSI-MEET system distinguishes between continuous streams, where values of different types come at a specified data rate, and discrete streams where sources push values intermittently. In MSDL, any dependence declaration must have at least one dependency specifying predicate in the body. As stream declarations are registered, the stream constraints are interpreted to construct a set of evaluation directives.
8364982
Supporting Complex Multi-Dimensional Queries in P2P Systems
More and more applications require peer-to-peer (P2P) systems to support complex queries over multi-dimensional data. For example, a P2P auction network for real estate frequently needs to answer queries such as "select five available buildings closest to the airport". Such queries are not efficiently supported in current P2P systems. Towards an efficient and scalable P2P system capable of processing complex multi-dimensional queries, the authors first proposed a comprehensive framework for sharing, indexing, and querying multi-dimensional data, where (i) peers with more computational power coordinate indexing and query processing, and (ii) other peers participate in part of the computation in order to achieve scalability and load-balance. Based on this framework, Network-R-tree (NR-tree), a P2P adaptation of the dominant spatial index - R*-tree was proposed. NR-tree, indexing spatial data at clustered peers, is capable of processing complex queries such as range queries and k-nearest neighbor queries. The authors proposed query processing algorithms for range and k-nearest neighbor queries and experimentally prove the effectiveness of proposed techniques with real data
3419561
A Dynamically Adaptive Distributed System for Processing Complex Continuous Queries
Recent years have witnessed rapidly growing research attention on continuous query processing over streams [2, 3]. A continuous query system can easily run out of resources in case of large amount of input stream data. Distributed continuous query processing over a shared nothing architecture, i.e., a cluster of machines, has been recognized as a scalable method to solve this problem [2, 8, 9]. Due to the lack of initial cost information and the fluctuating nature of the streaming data, uneven workload among machines may occur and this may impair the benefits of distributed processing. Thus dynamic adaptation techniques are crucial for a distributed continuous query system.
2849367
Temporal segmentation of video using frame and histogram space
Two algorithms are presented for the detection of gradual transitions in video sequences. The first is a dissolve detection algorithm utilizing certain properties of a dissolve's trajectory in image-space. It is implemented both as a simple threshold-based detector, and as a parametric detector by modeling the error properties of the extracted statistics. The second is an algorithm to detect a wide variety of wipes based on image histogram characteristics during such transitions. Both algorithms operate in the compressed domain, requiring only partial decoding of the compressed video stream. Experiments show the algorithms perform as well as-and in some cases, better than-full-frame methods, on a wide variety of gradual transitions, and can operate significantly faster than real-time.
10886416
Prediction and indexing of moving objects with unknown motion patterns
Existing methods for peediction spatio-temporal databases assume that objects move according to linear functions. This severely limits their applicability, since in practice movement is more complex, and individual objects may follow drastically diffferent motion patterns. In order to overcome these problems, we first introduce a general framework for monitoring and indexing moving objects, where (i) each boject computes individually the function that accurately captures its movement and (ii) a server indexes the object locations at a coarse level and processes queries using a filter-refinement mechanism. Our second contribution is a novel recursive motion function that supports a broad class of non-linear motion patterns. The function does not presume any a-priori movement but can postulate the particular motion of each object by examining its locations at recent timestamps. Finally. we propse an efficient indexing scheme that faciliates the processing of predicitive queries without false misses.
39083116
Data hiding in digital binary image
This paper proposes a new method to embed data in binary images, including scanned text, figures and signatures. The method manipulates "flippable" pixels and uses shuffling to embed a significant amount of data without causing noticeable artifacts. The extraction of the hidden data does not require the original image. Potential applications include detecting unauthorized use of a digitized signature and authenticating binary documents.