2 research outputs found
Semantics and planning based workflow composition and execution for video processing
Traditional workflow systems have several drawbacks, e.g. in their inabilities to rapidly
react to changes, to construct workflow automatically (or with user involvement) and
to improve performance autonomously (or with user involvement) in an incremental
manner according to specified goals. Overcoming these limitations would be highly
beneficial for complex domains where such adversities are exhibited. Video processing
is one such domain that increasingly requires attention as larger amounts of images and
videos are becoming available to persons who are not technically adept in modelling
the processes that are involved in constructing complex video processing workflows.
Conventional video and image processing systems, on the other hand, are developed
by programmers possessing image processing expertise. These systems are tailored
to produce highly specialised hand-crafted solutions for very specific tasks, making
them rigid and non-modular. The knowledge-based vision community have attempted
to produce more modular solutions by incorporating ontologies. However,
they have not been maximally utilised to encompass aspects such as application context
descriptions (e.g. lighting and clearness effects) and qualitative measures.
This thesis aims to tackle some of the research gaps yet to be addressed by the
workflow and knowledge-based image processing communities by proposing a novel
workflow composition and execution approach within an integrated framework. This
framework distinguishes three levels of abstraction via the design, workflow and processing
layers. The core technologies that drive the workflow composition mechanism
are ontologies and planning. Video processing problems provide a fitting domain for
investigating the effectiveness of this integratedmethod as tackling such problems have
not been fully explored by the workflow, planning and ontological communities despite
their combined beneficial traits to confront this known hard problem. In addition, the
pervasiveness of video data has proliferated the need for more automated assistance
for image processing-naive users, but no adequate support has been provided as of yet.
A video and image processing ontology that comprises three sub-ontologies was
constructed to capture the goals, video descriptions and capabilities (video and image
processing tools). The sub-ontologies are used for representation and inference. In
particular, they are used in conjunction with an enhanced Hierarchical Task Network
(HTN) domain independent planner to help with performance-based selection of solution
steps based on preconditions, effects and postconditions. The planner, in turn,
makes use of process models contained in a process library when deliberating on the
steps and then consults the capability ontology to retrieve a suitable tool at each step. Two key features of the planner are the ability to support workflow execution (interleaves
planning with execution) and can perform in automatic or semi-automatic
(interactive) mode. The first feature is highly desirable for video processing problems
because execution of image processing steps yield visual results that are intuitive
and verifiable by the human user, as automatic validation is non trivial. In the semiautomaticmode,
the planner is interactive and prompts the user tomake a tool selection
when there is more than one tool available to perform a task. The user makes the tool
selection based on the recommended descriptions provided by the workflow system.
Once planning is complete, the result of applying the tool of their choice is presented
to the user textually and visually for verification. This plays a pivotal role in providing
the user with control and the ability to make informed decisions. Hence, the planner
extends the capabilities of typical planners by guiding the user to construct more
optimal solutions. Video processing problems can also be solved in more modular,
reusable and adaptable ways as compared to conventional image processing systems.
The integrated approach was evaluated on a test set consisting of videos originating
from open sea environment of varying quality. Experiments to evaluate the efficiency,
adaptability to user’s changing needs and user learnability of this approach were conducted
on users who did not possess image processing expertise. The findings indicate
that using this integrated workflow composition and execution method: 1) provides a
speed up of over 90% in execution time for video classification tasks using full automatic
processing compared to manual methods without loss of accuracy; 2) is more
flexible and adaptable in response to changes in user requests (be it in the task, constraints
to the task or descriptions of the video) than modifying existing image processing
programs when the domain descriptions are altered; 3) assists the user in selecting
optimal solutions by providing recommended descriptions
Bridging the gap between business process models and service-oriented architectures with reference to the grid environment
In recent years, organisations have been seeking technological solutions for enacting their business process models using ad-hoc and heuristic approaches. However, limited results have been obtained due to the expansion of business processes across geographical boundaries and the absence of structured methods, frameworks and/or Information Technology (IT) infrastructures to enact these processes. In an attempt to enact business process models using distributed technologies, we introduce a novel architectural framework to bridge the gap between business process models and Grid-aware Service-Oriented Architectures (GSOA). BPMSOA framework is aligned with the Model-Driven Engineering (MDE) approach and is instantiated for role-based business process models [in particular Role Activity Diagramming (RAD)], using mobile process languages such as pi-ADL. The evaluation of the BPMSOA framework using the Submission process from the digital libraries domain has revealed that role-based business process models can be successfully enacted in GSOA environments with certain limitations. © 2011 Inderscience Enterprises Ltd