Understanding action concepts from videos and brain activity through subjects' consensus.

ABSTRACT: In this paper, we investigate brain activity associated with complex visual tasks, showing that electroencephalography (EEG) data can help computer vision in reliably recognizing actions from video footage that is used to stimulate human observers. Notably, we consider not only typical "explicit" video action benchmarks, but also more complex data sequences in which action concepts are only referred to, implicitly. To this end, we consider a challenging action recognition benchmark dataset-Moments in Time-whose video sequences do not explicitly visualize actions, but only implicitly refer to them (e.g., fireworks in the sky as an extreme example of "flying"). We employ such videos as stimuli and involve a large sample of subjects to collect a high-definition, multi-modal EEG and video data

SUBMITTER: Cavazza J 

PROVIDER: S-EPMC9646846 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature