A histogram-based approach for object-based query-by-shape-and-color in image and video databases

Considering the fact that querying by low-level object features is essential in image and video data, an efficient approach for querying and retrieval by shape and color is proposed. The approach employs three specialized histograms, (i.e. distance, angle, and color histograms) to store feature-based information that is extracted from objects. The objects can be extracted from images or video frames. The proposed histogram-based approach is used as a component in the query-by-feature subsystem of a video database management system. The color and shape information is handled together to enrich the querying capabilities for content-based retrieval. The evaluation of the retrieval effectiveness and the robustness of the proposed approach is presented via performance experiments. © 2005 Elsevier Ltd. All rights reserved

A database model for querying visual surveillance videos by integrating semantic and low-level features

Automated visual surveillance has emerged as a trendy application domain in recent years. Many approaches have been developed on video processing and understanding. Content-based access to surveillance video has become a challenging research area. The results of a considerable amount of work dealing with automated access to visual surveillance have appeared in the literature. However, the event models and the content-based querying and retrieval components have significant gaps remaining unfilled. To narrow these gaps, we propose a database model for querying surveillance videos by integrating semantic and low-level features. In this paper, the initial design of the database model, the query types, and the specifications of its query language are presented. © Springer-Verlag Berlin Heidelberg 2005

BilVideo: A video database management system

The BilVideo video database management system provides integrated support for spatiotemporal and semantic queries for video. BilVideo can support any application with video data searching needs. It's query language provides a simple way to extend the system's query capabilities. Users can add application-dependent rules and facts to the knowledge base

Keyframe labeling technique for surveillance event classification

The huge amount of video data generated by surveillance systems necessitates the use of automatic tools for their efficient analysis, indexing, and retrieval. Automated access to the semantic content of surveillance videos to detect anomalous events is among the basic tasks; however, due to the high variability of the audio-visual features and large size of the video input, it still remains a challenging task, though a considerable amount of research dealing with automated access to video surveillance has appeared in the literature. We propose a keyframe labeling technique, especially for indoor environments, which assigns labels to keyframes extracted by a keyframe detection algorithm, and hence transforms the input video to an event-sequence representation. This representation is used to detect unusual behaviors, such as crossover, deposit, and pickup, with the help of three separate mechanisms based on finite state automata. The keyframes are detected based on a grid-based motion representation of the moving regions, called the motion appearance mask. It has been shown through performance experiments that the keyframe labeling algorithm significantly reduces the storage requirements and yields reasonable event detection and classification performance. © 2010 Society of Photo-Optical Instrumentation Engineers

BilVideo: Design and implementation of a video database management system

With the advances in information technology, the amount of multimedia data captured, produced, and stored is increasing rapidly. As a consequence, multimedia content is widely used for many applications in today's world, and hence, a need for organizing this data, and accessing it from repositories with vast amount of information has been a driving stimulus both commercially and academically. In compliance with this inevitable trend, first image and especially later video database management systems have attracted a great deal of attention, since traditional database systems are designed to deal with alphanumeric information only, thereby not being suitable for multimedia data. In this paper, a prototype video database management system, which we call BilVideo, is introduced. The system architecture of BilVideo is original in that it provides full support for spatio-temporal queries that contain any combination of spatial, temporal, object-appearance, external-predicate, trajectory-projection, and similarity-based object-trajectory conditions by a rule-based system built on a knowledge-base, while utilizing an object-relational database to respond to semantic (keyword, event/activity, and category-based), color, shape, and texture queries. The parts of BilVideo (Fact-Extractor, Video-Annotator, its Web-based visual query interface, and its SQL-like textual query language) are presented, as well. Moreover, our query processing strategy is also briefly explained. © 2005 Springer Science + Business Media, Inc

Content-based retrieval of historical Ottoman documents stored as textual images

There is an accelerating demand to access the visual content of documents stored in historical and cultural archives. Availability of electronic imaging tools and effective image processing techniques makes it feasible to process the multimedia data in large databases. In this paper, a framework for content-based retrieval of historical documents in the Ottoman Empire archives is presented. The documents are stored as textual images, which are compressed by constructing a library of symbols occurring in a document, and the symbols in the original image are then replaced with pointers into the codebook to obtain a compressed representation of the image. The features in wavelet and spatial domain based on angular and distance span of shapes are used to extract the symbols. In order to make content-based retrieval in historical archives, a query is specified as a rectangular region in an input image and the same symbol-extraction process is applied to the query region. The queries are processed on the codebook of documents and the query images are identified in the resulting documents using the pointers in textual images. The querying process does not require decompression of images. The new content-based retrieval framework is also applicable to many other document archives using different scripts

Silhouette-based method for object classification and human action recognition in video

In this paper we present an instance based machine learning algorithm and system for real-time object classification and human action recognition which can help to build intelligent surveillance systems. The proposed method makes use of object silhouettes to classify objects and actions of humans present in a scene monitored by a stationary camera. An adaptive background subtracttion model is used for object segmentation. Template matching based supervised learning method is adopted to classify objects into classes like human, human group and vehicle; and human actions into predefined classes like walking, boxing and kicking by making use of object silhouettes. © Springer-Verlag Berlin Heidelberg 2006

Scenario-based query processing for video-surveillance archives

Automated video surveillance has emerged as a trendy application domain in recent years, and accessing the semantic content of surveillance video has become a challenging research area. The results of a considerable amount of research dealing with automated access to video surveillance have appeared in the literature; however, significant semantic gaps in event models and content-based access to surveillance video remain. In this paper, we propose a scenario-based query-processing system for video surveillance archives. In our system, a scenario is specified as a sequence of event predicates that can be enriched with object-based low-level features and directional predicates. We introduce an inverted tracking scheme, which effectively tracks the moving objects and enables view-based addressing of the scene. Our query-processing system also supports inverse querying and view-based querying, for after-the-fact activity analysis. We propose a specific surveillance query language to express the supported query types in a scenario-based manner. We also present a visual query-specification interface devised to facilitate the query-specification process. We have conducted performance experiments to show that our query-processing technique has a high expressive power and satisfactory retrieval accuracy in video surveillance. © 2009 Elsevier Ltd. All rights reserved

Content-based retrieval (CBR) system for ottoman archives [Osmanli arşivleri i̇çerik-Bazli sorgulama (İBS) sistemi]

We propose a content-based retrieval (CBR) system for digital Ottoman archive documents. In this system, the symbols extracted from the documents are matched with the most similar one in the symbol library, which is created in a supervised manner. The users specify queries by marking a region on an example document and the system retrieves all documents that include the symbols found in the query region. A prototype of the system is currently available on the Web. © 2006 IEEE