Perceptual Analysis

Perceptual analysis investigates how humans perceive and interpret sensory information, focusing on bridging the gap between subjective experience and objective measurement. Current research emphasizes developing and validating computational models of perception, often using deep learning architectures, to understand both human and machine processing of visual information (e.g., images, videos), auditory information (e.g., speech), and even higher-level concepts like personality traits inferred from visual cues. This work is crucial for improving applications ranging from image and speech processing to virtual reality and human-computer interaction by providing more accurate and realistic representations of the world as perceived by humans. The development of large-scale datasets and novel metrics for evaluating perceptual differences is also a key focus, enabling more robust and reliable comparisons across different models and systems.