Audio–Visual Sensor Fusion Strategies for Video Content Analytics II

Dear Colleagues,

A two-hour movie, or a short movie clip as its subset, is intended to capture and present a meaningful (or significant) story in video to be recognized and understood by a human audience. What if we substitute a human audience with that of an intelligent machine or robot capable of capturing and processing the semantic information in terms of audio and video cues contained in the video? The human brain processes audio (sound, speech) and video (background image scene, moving video objects, and written characters) modalities to extract spatial and temporal semantic information, which is contextually complementary and robust. Smart machines equipped with audiovisual multisensors (e.g., CCTV equipped with cameras and microphones) should be capable of achieving the same task. An appropriate fusion strategy combining the audio and visual information would be key in developing such artificial general intelligent (AGI) systems. This Special Issue calls for papers on various sensor fusion techniques to combine the audio–visual information cues for video content analytics. There can be a wide range of fusion strategies at various information levels (e.g., feature, decision, and semantic) to extract meaningful information by providing the attention mechanism in terms of weighting significance of the cue to represent the intended world. In light of recent advancements in deep-learning, this Special Issue will provide an important forum to present new fusion strategies by addressing the relevant research issues toward solving many applications requiring artificial general intelligence.

Prof. Dr. Hanseok Ko
Guest Editor

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