Citation
Affendey, Lilly Suriani
(2006)
Data Modeling and Hybrid Query for Video Database.
Doctoral thesis, Universiti Putra Malaysia.
Abstract
Video data management is important since the effective use of video in multimedia
applications is often impeded by the difficulty in cataloging and managing video data.
Major aspects of video data management include data modelling, indexing and querying.
Modelling is concerned with representing the structural properties of video as well as its
content. A video data model should be expressive enough to capture several
characteristics inherent to video. Depending on the underlying data model, video can
be indexed by text for describing semantics or by their low-level visual features such as
colour. It is not reasonable to assume that all types of multimedia data can be described
sufficiently with words alone. Although query by text annotations complements query
by low-level features, query formulation in existing systems is still done separately.
Existing systems do not support combination of these two types of queries since there
are essential differences between querying multimedia data and traditional databases.
These differences cause us to consider new types of queries. The purpose of this research is to model video data that would allow users to formulate
queries using hybrid query mechanism. In this research, we define a video data model
that captures the hierarchical structure and contents of video. Based on this data model,
we design and develop a Video Database System (VDBS). We compared query
formulation using single types against a hybrid query type. Results of the hybrid query
type are better than the single query types. We extend the Structured Query Language
(SQL) to support video functions and design a visual query interface for supporting
hybrid queries, which is a combination of exact and similarity-based queries.
Our research contributions include a video data model that captures the hierarchical
structure of video (sequence, scene, shot and key frame), as well as high-level concepts
(object, activity, event) and low-level visual features (colour, texture, shape and
location). By introducing video functions, the extended SQL supports queries on video
segments, semantic as well as low-level visual features. The hybrid query formulation
has allowed the combination of query by text and query by example in a single query
statement. We have designed a visual query interface that would facilitate the hybrid
query formulation. In addition we have proposed a video database system architecture
that includes shot detection, annotation and query formulation modules. Further works
consider the implementation and integration of these modules with other attributes of
video data such as spatio-temporal and object motion.
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