6,890 research outputs found

    Technological Progression and Procedures in Microsoft Kinect Sensor

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    Kinect is a sensor technology capable of tracking any environmental phenomena by sensing it for identification. And it plays a unique and vital role in the study of identification as it recognizes every object using the sensor. However, Kinect sensors track and sense objects using their color and data with the enhancement of tracking various actions and postures. Improvisations are inhabited within the technology based on identity, digitalization, alpha channels, depth of color and sensors in Autism research. Major concepts of Kinect sensor and its enhancement features are surveyed in this paper

    Face and Gesture Recognition for Human-Robot Interaction

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    Precision Livestock Farming Technologies for Pig Welfare - Policy Spotlight

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    Precision Livestock Farming Technologies for Pig Welfare - Policy Spotlight

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    Emotion Recognition in Horses with Convolutional Neural Networks

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    Creating intelligent systems capable of recognizing emotions is a difficult task, especially when looking at emotions in animals. This paper describes the process of designing a "proof of concept" system to recognize emotions in horses. This system is formed by two elements, a detector and a model. The detector is a fast region-based convolutional neural network that detects horses in an image. The model is a convolutional neural network that predicts the emotions of those horses. These two elements were trained with multiple images of horses until they achieved high accuracy in their tasks. In total, 400 images of horses were collected and labeled to train both the detector and the model while 40 were used to test the system. Once the two components were validated, they were combined into a testable system that would detect equine emotions based on established behavioral ethograms indicating emotional affect through head, neck, ear, muzzle and eye position. The system showed an accuracy of 80% on the validation set and 65% on the test set, demonstrating that it is possible to predict emotions in animals using autonomous intelligent systems. Such a system has multiple applications including further studies in the growing field of animal emotions as well as in the veterinary field to determine the physical welfare of horses or other livestock.Comment: 14 pages, 11figure

    Embedded System for Biometric Identification

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