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Proceedings Paper

A method to quantify movement activity of groups of animals using automated image analysis
Author(s): Jianyu Xu; Haizhen Yu; Ying Liu
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Paper Abstract

Most physiological and environmental changes are capable of inducing variations in animal behavior. The behavioral parameters have the possibility to be measured continuously in-situ by a non-invasive and non-contact approach, and have the potential to be used in the actual productions to predict stress conditions. Most vertebrates tend to live in groups, herds, flocks, shoals, bands, packs of conspecific individuals. Under culture conditions, the livestock or fish are in groups and interact on each other, so the aggregate behavior of the group should be studied rather than that of individuals. This paper presents a method to calculate the movement speed of a group of animal in a enclosure or a tank denoted by body length speed that correspond to group activity using computer vision technique. Frame sequences captured at special time interval were subtracted in pairs after image segmentation and identification. By labeling components caused by object movement in difference frame, the projected area caused by the movement of every object in the capture interval was calculated; this projected area was divided by the projected area of every object in the later frame to get body length moving distance of each object, and further could obtain the relative body length speed. The average speed of all object can well respond to the activity of the group. The group activity of a tilapia (Oreochromis niloticus) school to high (2.65 mg/L) levels of unionized ammonia (UIA) concentration were quantified based on these methods. High UIA level condition elicited a marked increase in school activity at the first hour (P<0.05) exhibiting an avoidance reaction (trying to flee from high UIA condition), and then decreased gradually.

Paper Details

Date Published: 11 July 2009
PDF: 7 pages
Proc. SPIE 7489, PIAGENG 2009: Image Processing and Photonics for Agricultural Engineering, 74891C (11 July 2009); doi: 10.1117/12.837187
Show Author Affiliations
Jianyu Xu, Ningbo Univ. (China)
Haizhen Yu, Ningbo Univ. (China)
Ying Liu, Institute of Oceanology (China)


Published in SPIE Proceedings Vol. 7489:
PIAGENG 2009: Image Processing and Photonics for Agricultural Engineering
Honghua Tan; Qi Luo, Editor(s)

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