Open Access
A Knowledge-Based Planner for Processing Unconstrained Underwater Videos
Gaya Nadarajan,Jessica Chen-Burger,Bob Fisher +2 more
- 01 Jan 2009
pp 37-44
TL;DR: An automated solution is implemented that makes use of formalisms for goaldirected behavior in the form of hierarchical task networks (HTNs) incorporated within a novel workflow composition framework that aims to assist naive users conduct complex video processing tasks automatically.
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Abstract: Video data collected continuously are pervasive today but analyzing them in an efficient manner has proven to be a challenge. This is because raw data is unlabelled and prone to noise, causing difficulty in extracting knowledge. With the aid of userprovided domain knowledge and heuristics used by image processing experts, an automated solution is implemented. It makes use of formalisms for goaldirected behavior in the form of hierarchical task networks (HTNs). These are incorporated within a novel workflow composition framework that aims to assist naive users conduct complex video processing tasks automatically. An example is illustrated for video classification, fish detection and fish counting in unconstrained underwater videos.
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Citations
FishNet: A Large-scale Dataset and Benchmark for Fish Recognition, Detection, and Functional Trait Prediction
Faizan Farooq Khan,Xiang Li,Andrew J. Temple,Mohamed Elhoseiny +3 more
- 01 Oct 2023
TL;DR: The FishNet dataset is presented, a large-scale diverse dataset containing 94,532 meticulously organized images from 17,357 aquatic species, organized according to aquatic biological taxonomy (order, family, genus, and species) to facilitate the development of aquatic species recognition systems, and promote further research in the field of aquatic ecology.
20
Semantics and Planning Based Workflow Composition for Video Processing
Gayathri Nadarajan,Yun-Heh Chen-Burger,Robert B. Fisher +2 more
- 01 Sep 2013
TL;DR: This work proposes a novel workflow composition approach that hinges upon ontologies and planning as its core technologies within an integrated framework that 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.
•Dissertation
Semantics and planning based workflow composition and execution for video processing
Gayathri Nadarajan
- 01 Jan 2011
TL;DR: This thesis aims to tackle some of the research gaps yet to be a ddr ssed by the workflow and knowledge-based image processing communities by proposing a novel workflow composition and execution approach within an integ rated framework.
7
SWAV: semantics-based workflows for automatic video analysis
Gayathri Nadarajan,Yun-Heh Chen-Burger,Robert B. Fisher +2 more
- 29 Jun 2011
TL;DR: An evaluation on a set of ecological videos has indicated that SWAV is more time-efficient at solving video classification tasks than manual processing and is more adaptable in response to changes in user requests than modifying existing image processing programs.
•Dissertation
Detection of unusual fish trajectories from underwater videos
Cigdem Beyan
- 29 Jun 2015
TL;DR: The proposed flat classifier, which uses an outlier detection method based on cluster cardinalities and a distance function to detect unusual fish trajectories, improved the performance of unusual fish detection compared to the filtering approach.
5
References
Scientific Workflow Management and the Kepler System
Bertram Ludäscher,Bertram Ludäscher,Ilkay Altintas,Chad Berkley,Dan Higgins,Efrat Jaeger,Matthew B. Jones,Edward A. Lee,Jing Tao,Yang Zhao +9 more
TL;DR: Kepler as mentioned in this paper is a scientific workflow system, which is currently under development across a number of scientific data management projects and is a community-driven, open source project, and always welcome related projects and new contributors to join.
OWL: Web Ontology Language
Sean Bechhofer
- 01 Jan 2009
TL;DR: The aim of this chapter is to present the Web ontology language (OWL) which can be used to develop Semantic Web applications that understand information and data on the Web.
665
•Proceedings Article
Detecting, tracking and counting fish in low quality unconstrained underwater videos
Concetto Spampinato,Yun-Heh Chen-Burger,Gayathri Nadarajan,Robert B. Fisher +3 more
- 01 Jan 2008
TL;DR: Unlike existing fish-counting methods, this approach provides a reliable method in which the fish number is computed in unconstrained environments and under several scenarios (murky water, algae on camera lens, moving plants, low contrast, etc.).