A Real World Dataset of Canine Emotions Using Video and Audio

The purpose of this collection was to investigate the feasibility of using both audio and visual data to recognize various dog emotions and lay the groundwork for automatic algorithms to recognize dog emotions. This data set has been gathered from various localities of Mangalore Approximately 127 audio-visual dog recordings collected for the study of Canine Emotion Recognition.

The dataset consists of 4 emotion classes of unlabelled video recordings of dog: Happy, Sad, Angry, and Relaxed., These emotions are identified and assigned labels through the application of various clustering algorithms.. The dataset will contribute to the research and development of machine learning and deep learning algorithms for understanding and categorizing the emotional state of dogs based on visual and auditory cues.