Application of the Particle Filter to Tracking of Fish in Aquaculture Research

Pinkiewicz, T.; Williams, RN; Purser, John

doi:10.1109/dicta.2008.28

Cited by 11 publications

(3 citation statements)

References 15 publications

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“…Available software to detect animal movements was not directly applicable to our experimental design and tank size. For example, the program of Pinkiewicz [30] allows the tracking of a fish school (larger fish swimming mainly in the same direction) but is not applicable to our experimental design and the small species of fish. As S .…”

Section: Methodsmentioning

confidence: 99%

Metabolic costs of spontaneous swimming in Sprattus sprattus L., at different water temperatures

Meskendahl¹,

Fontes²,

Herrmann³

et al. 2019

PLoS ONE

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Oxygen uptake (MO2; mgO2 fish-1h-1) of fish groups was measured at temperatures between 10–19°C in an intermittent-flow respirometer to quantify the metabolic costs of spontaneous swimming patterns in the small clupeid Sprattus sprattus. Movements of individual fish within the school were tracked automatically during respirometry. Oxygen uptake was then related to mean swimming speeds and the number of sharp turns (>90°), which are common behavioural elements of spontaneous swimming in clupeid fish. Different possible model formulations for describing the relationship between respiration and swimming patterns were compared via the AIC. The final model revealed that costs for sharp turns at a frequency of 1 s-1 doubled the metabolic costs compared to those with zero turns but with likewise a moderate swimming speed of 0.28 body length -1. The cost for swimming doubled if the swimming speed was doubled from 0.28 to 0.56 BLs-1 but increased by a factor of 4.5 if tripled to 0.84 BLs-1. Costs for transport were minimal at a speed of 0.4 body lengths s-1 at all temperatures. New basic input parameters to estimate energy losses during spontaneous movements, which occur typically during foraging in this small pelagic fish, are provided.

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Section: Methodsmentioning

confidence: 99%

Metabolic costs of spontaneous swimming in Sprattus sprattus L., at different water temperatures

Meskendahl¹,

Fontes²,

Herrmann³

et al. 2019

PLoS ONE

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show abstract

“…The multitracking system tracked the fish movements by predicting the theoretical position of each individual and matched to the nearest neighbor of the target fish (Delcourt et al, 2009). A Kalman filter and particle filter are the most widely used techniques for predicting the positions of moving targets for tracking tasks, including the movement tracking of multiple fish (Fontaine et al, 2008;Pinkiewicz et al, 2008;). Recently, more sophisticated tracking techniques have been developed to improve the performance of behavioral analysis of fish and the maximal number of targets is up to 50 individuals for 2D tracking (Branson et al, 2009;Papadakis et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Posture tracking of multiple individual fish for behavioral monitoring with visual sensors

Xia

Chon

Liu

et al. 2016

Ecological Informatics

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a b s t r a c t a r t i c l e i n f oArticle history: Received 8 January 2015 Received in revised form 7 July 2016 Accepted 12 July 2016 Available online xxxx A novel scheme for the behavioral monitoring of multiple fish is presented based on measurements of the fish posture. Image identification of the fish head and tail is proposed by examining the gray level appearance features. A simplified posture of fish was calculated from its head and centroid. Multiple individual tracking was developed by incorporating the fish posture and global nearest neighbor. The proposed tracking scheme was tested with 2-5 individual Zebra fish (Cyprinidae, Danio rerio) under laboratory conditions. The experimental results confirmed the stability of the identification of a fish head and tail and a robust tracking performance was achieved. The proposed method could accurately record the movement trajectories and posture information of each individual. The tracking errors were only 0.278%-1.572% for 2-5 individual fish while the posture measurement error rates were less than 0.16%. Furthermore, the movement patterns of the fish, e.g., angular variations and distribution of the movement angle, were investigated from the behavioral data, which revealed the advantages of the proposed posture measurement for behavioral studies. The aggregation behavior of multiple fish was also analyzed to reveal the interaction patterns of the individuals in response to the spatial formation of the neighbors.

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“…But the object modeling method is too complex, and requires more system memory; it is hard for actual monitoring applications due to poor real-time ability. A tracking system is introduced in Pinkiewicz, Williams, and Purser (2008) which can automatically detect and track two fish in a video sequence in a small aquaculture tank. The system is based on the particle filter tracking algorithm augmented by an adaptive partition scheme and using a Global Nearest Neighbor approach for data association.…”

Section: Introductionmentioning

confidence: 99%

Data Association Based Tracking Traffic Objects

Gao

2013

International Journal of Advanced Pervasive and Ubiquitous Computing

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For the widely demanding of adaptive multiple moving objects tracking in intelligent transportation field, a new type of traffic video based multi-object tracking method is presented. Background is modeled by difference of Gaussians (DOG) probability kernel and background subtraction is used to detect multiple moving objects. After obtaining the foreground, shadow is eliminated by an edge detection method. A type of particle filtering combined with SIFT method is used for motion tracking. A queue chain method is used to record data association among different objects, which could improve the detection accuracy and reduce the complexity. By actual road tests, the system tracks multi-object with a better performance of real time and mutual occlusion robustness, indicating that it is effective for intelligent transportation system.

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Application of the Particle Filter to Tracking of Fish in Aquaculture Research

Abstract: Abstract

Cited by 11 publications

References 15 publications

Metabolic costs of spontaneous swimming in Sprattus sprattus L., at different water temperatures

Metabolic costs of spontaneous swimming in Sprattus sprattus L., at different water temperatures

Posture tracking of multiple individual fish for behavioral monitoring with visual sensors

Data Association Based Tracking Traffic Objects

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