Representation and Analysis of Multimedia Content: The BOEMIE Proposal Software & Knowledge Engineering Laboratory Institute of Informatics & Telecommunications NCSR “Demokritos”, Athens, Greece Representation and Analysis of Multimedia Content: The BOEMIE Proposal D.I. Kosmopoulos, V. Karkaletsis, S. Perantonis, G. Paliouras, C.D. Spyropoulos LREC Workshop “Crossing media for improved information access” Genoa, 23 May 2006

Contents Multimedia content analysis Existing approaches BOEMIE proposal Application scenario Concluding remarks BOEMIE proposal LREC Crossing Media Workshop, Genoa, 23/05/2006

Multimedia Content Analysis - I Multimedia content grows with increasing rates Hard to provide semantic indexing of multimedia content Significant advances in automatic extraction of low-level features from visual content Little progress in the identification of high- level semantic features BOEMIE proposal LREC Crossing Media Workshop, Genoa, 23/05/2006

Multimedia Content Analysis - II Inadequate the analysis of single modalities Little progress in the effective combination of semantic features from different modalities. Significant effort in producing ontologies for semantic webs. Hard to build and maintain domain- specific multimedia ontologies. BOEMIE proposal LREC Crossing Media Workshop, Genoa, 23/05/2006

Existing approaches - I Combination of modalities may serve as a verification method, a method compensating for inaccuracies, or as an additional information source Combination methods may be iterated allowing for incremental use of context Major open issues in combination concern the efficient utilization of prior knowledge, the specification of open architecture for the integration of information from multiple sources, and the use of inference tools BOEMIE proposal LREC Crossing Media Workshop, Genoa, 23/05/2006

Existing approaches - II Most of the extraction approaches are based on machine learning methods With the advent of promising methodologies in multimedia ontology engineering knowledge-based approaches are expected to gain in popularity and be combined with the machine learning methods BOEMIE proposal LREC Crossing Media Workshop, Genoa, 23/05/2006

Existing approaches – III Use of Ontologies to “drive” the information extraction process providing high-level semantic information that helps disambiguating the labels assigned to MM objects Major open issues in building and maintaining MM ontologies concern automatic mapping between low level audio-visual features and high level domain concepts, automated population and enrichment from unconstrained content, employing of ontology coordination techniques when multiple ontologies are present BOEMIE proposal LREC Crossing Media Workshop, Genoa, 23/05/2006

Existing approaches - IV Synergy between information extraction and ontology learning through a bootstrapping process to improve both the conceptual model and the extraction system through iterative refinement Applied so far in knowledge acquisition from textual content bootstrapping starts with an information extraction system that uses a domain ontology, or bootstrapping starts with a seed ontology, usually small BOEMIE proposal LREC Crossing Media Workshop, Genoa, 23/05/2006

BOEMIE project Bootstrapping Ontology Evolution with Multimedia Information Extraction STRP, IST-2004-2.4.7 “Semantic-based Knowledge and Content Systems” Started: 01/03/2006, Duration: 36 months Consortium Inst. of Informatics & Telecommunications, NCSR “Demokritos” (SKEL & CIL), Greece (Coordinator) Fraunhofer Institute for Media Communication (NetMedia), Germany Dip. di Informatica e Comunicazione, University of Milano (ISLab), Italy Inst. of Telematics and Informatics CERTH (IPL), Greece Hamburg University of Technology (STS), Germany Tele Atlas, Belgium BOEMIE proposal LREC Crossing Media Workshop, Genoa, 23/05/2006

BOEMIE proposal - I Driven by domain-specific multimedia ontologies, BOEMIE systems will be able to identify high-level semantic features in image, video, audio and text and fuse these features for optimal extraction. The ontologies will be continuously populated and enriched using the extracted semantic content. This is a bootstrapping process, since the enriched ontologies will in turn be used to drive the multimedia information extraction system. BOEMIE proposal LREC Crossing Media Workshop, Genoa, 23/05/2006

BOEMIE Proposal - II EVOLVED ONTOLOGY INITIAL POPULATION & ENRICHMENT COORDINATION INTERMEDIATE ONTOLOGY EVOLUTION TOOLKIT LEARNING TOLS REASONING ENGINE MATCHING TOOLS ONTOLOGY MANAGEMENT TOOL ONTOLOGY INITIALIZATION AND CONTENT MANAGEMENT TOOL ONTOLOGY EVOLUTION EVENTS DATABASE MAPS MAP ANNOTATION INTERFACE SEMANTICS EXTRACTION RESULTS OTHER ONTOLOGIES SEMANTICS EXTRACTION MULTIMEDIA CONTENT SEMANTICS EXTRACTION TOOLKIT TEXT EXTRACTION TOOLS AUDIO EXTRACTION TOOLS INFORMATION FUSION TOOLS VISUAL EXTRACTION TOOLS FROM VISUAL CONTENT FROM NON-VISUAL CONTENT FROM FUSED CONTENT Content Collection (crawlers, spiders, etc.) BOEMIE proposal LREC Crossing Media Workshop, Genoa, 23/05/2006

BOEMIE proposal - III Semantics extraction Emphasis to visual content, from images and video, due to its richness and the difficulty of extracting useful information. Non-visual content, audio/speech and text, will provide supportive evidence, to improve extraction precision. Fusing information from multiple media sources is needed since no single modality is powerful enough to encompass all aspects of the content and identify concepts precisely. BOEMIE proposal LREC Crossing Media Workshop, Genoa, 23/05/2006

BOEMIE proposal - IV Multimedia Ontologies development of a unifying representation, a “multimedia semantic model” to integrate: a multimedia ontology which describes the structure of multimedia content (content objects, such as a segment in a static image, a time window in audio, a video shot, ...), describes visual characteristics of content objects in terms of low-level features (colour, shape, texture, motion, …) a domain ontology which contains knowledge about the selected application domain, and a geographic ontology which contains additional knowledge about the locations to be used BOEMIE proposal LREC Crossing Media Workshop, Genoa, 23/05/2006

BOEMIE proposal – V Ontology evolution involves ontology population and enrichment, i.e., addition of concepts, relations, properties and instances, coordination of homogeneous ontologies e.g. when more than one ontology for the same domain are available, and heterogeneous ontologies, e.g., updating the links between a modified domain ontology and a multimedia descriptor ontology, maintenance of semantic consistency any of the above changes may generate inconsistencies in other parts of the same ontology, in the linked ontologies or in the annotated content base. BOEMIE proposal LREC Crossing Media Workshop, Genoa, 23/05/2006

Application scenario - I Enrichment of digital maps with semantic information Domain: sport events in a given area (big cities) Sub-domain initially selected: athletics (running, jumping and throwing events) Cities will be selected taking into account: number and frequency of sports events, availability of multimedia coverage in English of these events, availability of map and landmark data for the city BOEMIE will collect multimedia coverage for sport events and strive to extract as much knowledge from the extracted features as possible, using and evolving the corresponding domain ontologies The identified entities and their properties, will be linked to geographical locations and stored in a content server The user will be provided with immediate access to the annotated content BOEMIE proposal LREC Crossing Media Workshop, Genoa, 23/05/2006

Application scenario - II Functionality of the BOEMIE prototype Ontology initialization In the first phase, a domain ontology for the selected athletics domain will be created. The concepts of this ontology will be populated using low-level multimedia features. In the first phase, these features are extracted and linked to the ontology through manual content annotation. Suitable multimedia content for this purpose will be collected and stored in a multimedia repository. The manual content annotation and ontology initialization will be performed using existing tools. BOEMIE proposal LREC Crossing Media Workshop, Genoa, 23/05/2006

Application scenario - III Functionality of the BOEMIE prototype: semantics extraction The initial ontology will be used to train the classification and extraction components Once the training is completed, BOEMIE system will operate automatically to extract meta data and features from MM content Manual annotation will be used occasionally to train the system for new features BOEMIE proposal LREC Crossing Media Workshop, Genoa, 23/05/2006

Application scenario - IV Functionality of the BOEMIE prototype: semantics extraction, example of a fusion approach BOEMIE proposal LREC Crossing Media Workshop, Genoa, 23/05/2006

Application scenario - V Querying The prototype will perform reasoning using knowledge from the domain ontology and geographical knowledge to deduce further information and answer user queries. The user will be able to perform the following queries: events in a time frame events of a particular type events at a certain location persons related to events events similar to a given one events at nearby venues points of interest near a venue combinations of the above BOEMIE proposal LREC Crossing Media Workshop, Genoa, 23/05/2006

Application scenario - VI Querying: an example Find out the location of the venues in which Athlete A has participated in a high jump competition in the city X. From transcribed radio commentary, the BOEMIE system knows that in 2001, the World Championships in Athletics were held in city X in venue Y. From the geographical data, it knows the exact location of venue Y in city X. It has further analyzed a video snippet and identified it as a high jump event. From the meta data of the video, the system knows its date of recording in 2001, and in the audio of this snippet, the keywords “X” and A's name were spotted. Therefore, the system can deduce that A has indeed participated in a high jump competition in city X, namely the World Championships in Athletics 2001. As a result, the BOEMIE system presents all used multimedia assets as “prove” for its answer and gives the exact location of the venue where the World Championship in Athletics took place. BOEMIE proposal LREC Crossing Media Workshop, Genoa, 23/05/2006

Concluding remarks - I BOEMIE work aims to initiate a discussion on the problem of knowledge acquisition and the synergy of information extraction and ontology evolution Several open issues: the role of ontology in fusing information from multiple media ways to learn the optimal combination of features derived from MM content how existing ontology languages can be extended to tackle the requirements of MM content analysis the application of existing ontology learning and inference techniques in the context of MM content the application of the coordination task in a new context which involves not only homogeneous ontologies, but also heterogeneous ones BOEMIE proposal LREC Crossing Media Workshop, Genoa, 23/05/2006

Concluding remarks - II The main measurable objective of BOEMIE initiative is to improve significantly the performance of existing single-modality approaches in terms of scalability and precision. Towards that goal, our aim is to develop a new methodology for extraction and evolution, using a rich multimedia semantic model, and realize it as an open architecture that will be coupled with the appropriate set of tools. BOEMIE proposal LREC Crossing Media Workshop, Genoa, 23/05/2006

Representation and Analysis of Multimedia Content: The BOEMIE Proposal http://www.boemie.org D.I. Kosmopoulos, V. Karkaletsis, S. Perantonis, G. Paliouras, C.D. Spyropoulos THANK YOU !!! BOEMIE proposal LREC Crossing Media Workshop, Genoa, 23/05/2006