Perception operates on an immense amount of incoming information that greatly exceeds
the brain's processing capacity. Because of this fundamental limitation, the ability to …

Recently, increasing attention has been paid to the detection of spatio-temporal interest
points (STIPs), which has become a key technique and research focus in the field of …

Robust spatiotemporal representations of natural videos have several applications including
quality assessment, action recognition, object tracking etc. In this paper, we propose a video …

We present a novel action recognition method based on space-time locally adaptive
regression kernels and the matrix cosine similarity measure. The proposed method uses a …

Spatial Gabor energy filters (GE) are one of the most successful approaches to represent
facial expressions in computer vision applications, including face recognition and …

Segregation of objects from their backgrounds is a fundamental visual function and one that
is particularly effective when objects are in motion. Theoretically, suppressive center …

Understanding the brain's perception algorithm is a highly intricate problem, as the inherent
complexity of sensory inputs and the brain's nonlinear processing make characterizing …

Feature representation is an important research topic in facial expression recognition from
video sequences. In this letter, we propose to use spatiotemporal monogenic binary patterns …

Understanding how biological visual systems process information is challenging due to the
complex nonlinear relationship between neuronal responses and high-dimensional visual …

In this paper, we propose a bioinspired model for human action recognition through
modeling neural mechanisms of information processing in two visual cortical areas: the …