Automated event detection in underwater video

Edgington, D.R.; Salamy, Karen A.; Risi, M.; Sherlock, Rob E.; Walther, Dirk; Koch, Christof

doi:10.1109/oceans.2003.178344

Cited by 46 publications

(25 citation statements)

References 6 publications

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“…In particular, Edgington et al [17] proposed a system operating on the deep ocean where interesting low-level events (i.e. rare animals) are identified by using a model for saliency-based attention in humans and then such events are tracked.…”

Section: Event Detection In Underwater Scenesmentioning

confidence: 99%

Understanding fish behavior during typhoon events in real-life underwater environments

Spampinato

Palazzo

Boom

et al. 2012

Multimed Tools Appl

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The study of fish populations in their own natural environment is a task that has usually been tackled in invasive ways which inevitably influenced the behavior of the fish under observation. Recent projects involving the installation of permanent underwater cameras (e.g. the Fish4Knowledge (F4K) project, for the observation of Taiwan's coral reefs) allow to gather huge quantities of video data, without interfering with the observed environment, but at the same time require the development of automatic processing tools, since manual analysis would be impractical for such amounts of videos. Event detection is one of the most interesting This research was funded by European Commission FP7 grant 257024, for the Fish4Knowledge project (www.fish4knowledge.eu). Appl (2014) 70:199-236 aspects from the biologists' point of view, since it allows the analysis of fish activity during particular events, such as typhoons. In order to achieve this goal, in this paper we present an automatic video analysis approach for fish behavior understanding during typhoon events. The first step of the proposed system, therefore, involves the detection of "typhoon" events and it is based on video texture analysis and on classification by means of Support Vector Machines (SVM). As part of our behavior understanding efforts, trajectory extraction and clustering have been performed to study the differences in behavior when disruptive events happen. The integration of event detection with fish behavior understanding surpasses the idea of simply detecting events by low-level features analysis, as it supports the full semantic comprehension of interesting events.

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Section: Event Detection In Underwater Scenesmentioning

confidence: 99%

Understanding fish behavior during typhoon events in real-life underwater environments

Spampinato

Palazzo

Boom

et al. 2012

Multimed Tools Appl

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“…Change detection from images of the same scene captured at different time instances is of special interest in many image processing application areas such as video surveillance [1], satellite imaging [2], [3],medical image analysis [4], material analysis [5], underwater imaging [6], and driver assistance systems [7]. Remote sensing has long been used as a means of observing, monitoring, and understanding trajectories of changes in the condition of the Earth over time including natural and anthropogenic perturbation, climate change, and urbanisation.…”

Section: Introductionmentioning

confidence: 99%

Self-adaptive hybrid PSO-GA method for change detection under varying contrast conditions in satellite images

Kusetoğulları

Yavariabdi

2016

2016 SAI Computing Conference (SAI)

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Abstract-This paper proposes a new unsupervised satellite change detection method, which is robust to illumination changes. To achieve this, firstly, a preprocessing strategy is used to remove illumination artifacts and results in less false detection than traditional threshold-based algorithms. Then, we use the corrected input data to define a new fitness function based on the difference image. The purpose of using Self-Adaptive Hybrid Particle Swarm Optimization-Genetic Algorithm (SAPSOGA) is to combine two meta-heuristic optimization algorithms to search and find the feasible solution in the NP-hard change detection problem rapidly and efficiently. The hybrid algorithm is employed by letting the GA and PSO run simultaneously and similarities of GA and PSO have been considered to implement the algorithm, i.e. the population. In the SAPSOGA employed, in each iteration/generation the two population based algorithms share different amount of information or individual(s) between themselves. Thus, each algorithm informs each other about their best optimum results (fitness values and solution representations) which are obtained in their own population. The fitness function is minimized by using binary based SAPSOGA approach to produce binary change detection masks in each iteration to obtain the optimal change detection mask between two multi temporal multi spectral landsat images. The proposed approach effectively optimizes the change detection problem and finds the final change detection mask.

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“…Landis, Nagy, Keane, and Nagy (1999) used high-resolution 3D scanning techniques to measure internal damages and crack growth in a small mortar cylinder by analyzing same specimen at different levels of deformation and loadings. Underwater surveillance video frames from remotely operated underwater vehicles were used to track interesting or mundane objects which helped in sorting interesting objects (Edgington, Dirk, Salamy, Koch, Risi, Sherlock, 2003). In recent years, the concept of change detection through images has been extensively used for medical diagnosis.…”

Section: Introductionmentioning

confidence: 99%

Image-Based Change Detection for Bridge Inspection

Adhikari¹,

Moselhi²,

Bagchi³

2013

Proceedings of the 30th International Symposium on Automation and Robotics in Construction and Mining (ISARC 2013): Building Th

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The changes in defects patterns or in element condition index during visual inspection of bridges are primary concerns for inspectors. This paper presents a new approach for change detection of defects in bridges by identifying changes in texture patterns through spectral analysis of digital images. The commonly used method for change detection is image differentiation. This subtraction method requires images to be of same size, scale, and rotation. However, no two images are same in real practices. Thus, image registration is required to align images and to produce change maps. This process is tedious and it is difficult often to achieve a good registered image. But, the change detection task can be readily modeled in frequency domain for texture patterns discrimination and also for quantifying their properties. This paper proposes a novel approach for change detection by transforming digital images into Fourier spectrum. In new coordinate system, 1-D signature functions can be drawn which facilitates easy comparison of textures in different directions. The proposed methodology provides useful tools for comparison of inspection history graphically and quantitatively. In practice, expensive sensors are used to detect subtle change in defect patterns. The proposed method can be used to detect any subtle change in defect patterns using digital images at much lower cost.

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Automated event detection in underwater video

Cited by 46 publications

References 6 publications

Understanding fish behavior during typhoon events in real-life underwater environments

Understanding fish behavior during typhoon events in real-life underwater environments

Self-adaptive hybrid PSO-GA method for change detection under varying contrast conditions in satellite images

Image-Based Change Detection for Bridge Inspection

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