Journal of Engineering and Applied Sciences
ISSN: Online 1818-7803ISSN: Print 1816-949x
Abstract
Automated analysis of human affective behavior has attracted increasing attention from researchers in psychology, computer science, linguistics, neuroscience and related disciplines. However, the existing methods typically handle only deliberately displayed and exaggerated expressions of prototypical emotions, despite the fact that deliberate behavior differs in visual appearance, audio profile and timing from spontaneously occurring behavior. The goal of the challenge is to provide a common Benchmark test set for multimodal information processing and to bring together the audio, video and physiological emotion recognition communities to compare the relative merits of the three approaches to emotion recognition under well-defined and strictly comparable conditions and establish to what extent fusion of the approaches is possible and beneficial. This study presents the challenge, the dataset and the performance of the baseline system.
How to cite this article:
D. Lakshmi and R. Ponnusamy. Affect Recognition Challenge Bridging Across Audio,
Video and Physiological Data.
DOI: https://doi.org/10.36478/jeasci.2017.1864.1870
URL: https://www.makhillpublications.co/view-article/1816-949x/jeasci.2017.1864.1870