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Huan-Yu Chen, Chuen-Horng Lin, Jyun-Wei Lai and Yung-Kuan Chan
This paper proposes a multi?convolutional neural network (CNN)-based system for the detection, tracking, and recognition of the emotions of dogs in surveillance videos. This system detects dogs in each frame of a video, tracks the dogs in the video, and ...
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Meg Christophers, Lauren Heng and Nicholas Heng
Members of the genus Streptococcus inhabit a variety of sites in humans and other animals and some species are prolific producers of proteinaceous antibiotics (bacteriocins). As little is known about (i) streptococci inhabiting domestic pets, and (ii) wh...
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Jinah Kim and Nammee Moon
Although various studies on monitoring dog behavior have been conducted, methods that can minimize or compensate data noise are required. This paper proposes multimodal data-based dog behavior recognition that fuses video and sensor data using a camera a...
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Kim Ferres, Timo Schloesser and Peter A. Gloor
This paper describes an emotion recognition system for dogs automatically identifying the emotions anger, fear, happiness, and relaxation. It is based on a previously trained machine learning model, which uses automatic pose estimation to differentiate e...
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Satyabrata Aich, Sabyasachi Chakraborty, Jong-Seong Sim, Dong-Jin Jang and Hee-Cheol Kim
The safety and welfare of companion animals such as dogs has become a large challenge in the last few years. To assess the well-being of a dog, it is very important for human beings to understand the activity pattern of the dog, and its emotional behavio...
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Selwyn A. Headley, Alexandre M. Amude, Alice F. Alfieri, Ana Paula F.R.L. Bracarense, Amauri A. Alfieri, and Brian A. Summers
Selwyn A. Headley, Alexandre M. Amude, Alice F. Alfieri, Ana Paula F.R.L. Bracarense, Amauri A. Alfieri, and Brian A. Summ
Pág. 588 - 597
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