1980
DOI: 10.3758/bf03201828
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Pattern recognition of behavioral events in the nonhuman primate

Abstract: A computerized pattern recognition system has been developed that is capable of identifying 40 separate spontaneously occurring behavioral acts of the primate Macaca fascicularis. The system, called PROBE (pattern recognition of behavioral events), is described in detail. In its present stage of development, PROBE classifies behavioral activity with a reliability comparable to trained human observers. The potential applications for and improvements to the PROBE system are discussed.Techniques used in computer … Show more

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Cited by 11 publications
(3 citation statements)
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“…In its current implementation, EthoVision is able to detect whether an animal is moving or whether a rodent is rearing, but (in common with other commercial systems) it cannot automatically detect other body postures or behavioral patterns (unless, of course, it is possible to define them in terms of the existing parameters). Research on automatic classification of body postures and behavioral acts in digitized video sequences was already in progress more than two decades ago (Kernan et al, 1980) but has not, to our knowledge, found its way into a commercial product so far. Recently, however, considerable progress has been made with the use of model-based pattern recognition, statistical classification, and neural networks to automatically detect rodent behaviors, such as sitting, grooming, and stretched attend (Rousseau, van Lochem, Gispen, & Spruijt, 2000;van Lochem, Buma, Rousseau, & Noldus, 1998).…”
Section: Future Developmentsmentioning
confidence: 99%
“…In its current implementation, EthoVision is able to detect whether an animal is moving or whether a rodent is rearing, but (in common with other commercial systems) it cannot automatically detect other body postures or behavioral patterns (unless, of course, it is possible to define them in terms of the existing parameters). Research on automatic classification of body postures and behavioral acts in digitized video sequences was already in progress more than two decades ago (Kernan et al, 1980) but has not, to our knowledge, found its way into a commercial product so far. Recently, however, considerable progress has been made with the use of model-based pattern recognition, statistical classification, and neural networks to automatically detect rodent behaviors, such as sitting, grooming, and stretched attend (Rousseau, van Lochem, Gispen, & Spruijt, 2000;van Lochem, Buma, Rousseau, & Noldus, 1998).…”
Section: Future Developmentsmentioning
confidence: 99%
“…When extended to frame-by-frame playback, where software speed is not as critical, digitized video can also be used for more complex analyses of behavior. For example, items from a repertoire of behavioral fragments can be identified by matching an animal's posture to a series of stereotyped templates (Kernan et al, 1980). Eventually, image-recognition techniques, now much too slow for practical use, may bring the benefits of artificial intelligence to the automated analysis of behavior.…”
Section: Monitoring the Position Of An Appendagementioning
confidence: 99%
“…Although the system does not have the patternrecognition capabilities of the apparatus described by Kernan, Higby, Hopper, Cunningham, Lloyd, and Reiter (1980), it is effective for collecting data related to animal position and movement at a fraction of the cost. It is unlikely that this system could be programmed to recognize more than the simplest patterns because of the relatively low resolution of the camera and the slow processor speed, which hampers real-time analysis of large data sets.…”
Section: Image Digitiza Non By Microcomputer 349mentioning
confidence: 99%