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- W2468103639 abstract "Training animals is a process that requires a significant investment of time and energy on the part of the trainer. One of the most basic training tasks is to train dogs to perform postures on cue. While it might be easy for a human trainer to see when an animal has performed the desired posture, it is much more difficult for a computer to determine this. Most work in this area uses accelerometer and/or gyroscopic data to produce data from an animal's current state, but this has limitations. Take for example a normal standing posture. From an accelerometer's perspective, it closely resembles the laying down posture, but the posture can look very different if the animal is standing still, versus walking, versus running, and might look completely different from a standing on incline posture. A human trainer can instantly tell the difference between these postures and behaviors, but the process is much more difficult for a computer." @default.
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- W2468103639 date "2015-11-16" @default.
- W2468103639 modified "2023-10-07" @default.
- W2468103639 title "Knowledge engineering for unsupervised canine posture detection from IMU data" @default.
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- W2468103639 doi "https://doi.org/10.1145/2832932.2837015" @default.
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