Attending Prominent Face in the Set of Multiple Faces Through Relative Visual Saliency

Visual saliency determines the extent of attentiveness of a region in a scene. In the context of attending faces in the crowd, face components and its dominance features decide the focus on attention. Attention boosts up the recognition and identification process in a crowd and hence plays an excelling role in the area of visual surveillance and robotic vision. Using different computer vision-based techniques, enormous researches have been carried out on attention, recognition, and identification of the human face in context of different applications. This paper proposes a novel technique to analyze and explore the prominent face in the set of multiple faces (crowd). The proposed method stretched out the solution, using the concept of relative visual saliency, which has been evaluated on the various parameters of face as a whole and its componentwise too. These parameters are face area, spatial location, intensity, hue, RGB values, etc. The proposed work furnishes satisfactory results. The assessment made with this approach shows quite encouraging results which may lead to a future model for robotic vision and intelligent decision-making system.