Pointing Direction Estimation for Attention Target Extraction Using Body-mounted Camera

In this paper, we propose a pointing-directionestimation method using a body-mounted camera. The opportunities to capture a large amount of image data in daily life are increasing due to the spread of smartphones and wearable cameras. In order to efficiently look back at the captured images, we aim to extract attention targets from the image sequences because the attention target is important for reminding people of their memories. Toward this purpose, in this paper, we propose a method for estimating the pointing direction from wearable camera images. The proposed method consists of two steps: arm skeleton estimation and pointing direction estimation. We model three types of pointing-directionestimation models and compare the estimations' accuracy for evaluating which parts are important for pointing direction estimation. The experimental results show that the model based on the wrists and elbows had the best results.