2134/9955508.v1 Haibin Cai Haibin Cai Bangli Liu Bangli Liu Jianhua Zhang Jianhua Zhang Shengyong Chen Shengyong Chen Honghai Liu Honghai Liu Visual focus of attention estimation using eye center localization Loughborough University 2019 Convolution Eye center localization Human–robot interaction Integrodifferential Visual focus of attention (VFOA) 2019-10-09 09:10:03 Journal contribution https://repository.lboro.ac.uk/articles/journal_contribution/Visual_focus_of_attention_estimation_using_eye_center_localization/9955508 Estimating people visual focus of attention (VFOA) plays a crucial role in various practical systems such as human-robot interaction. It is challenging to extract the cue of the VFOA of a person due to the difficulty of recognizing gaze directionality. In this paper, we propose an improved integrodifferential approach to represent gaze via efficiently and accurately localizing the eye center in lower resolution image. The proposed method takes advantage of the drastic intensity changes between the iris and the sclera and the grayscale of the eye center as well. The number of kernels is optimized to convolute the original eye region image, and the eye center is located via searching the maximum ratio derivative of the neighbor curve magnitudes in the convolution image. Experimental results confirm that the algorithm outperforms the state-of-the-art methods in terms of computational cost, accuracy, and robustness to illumination changes.