TY - GEN
T1 - Extended gaze following
T2 - 14th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2019
AU - Massé, Benoit
AU - Lathuilière, Stéphane
AU - Mesejo, Pablo
AU - Horaud, Radu
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/5/1
Y1 - 2019/5/1
N2 - In this paper we address the problems of detecting objects of interest in a video and of estimating their locations, solely from the gaze directions of people present in the video. Objects can be indistinctly located inside or outside the camera field of view. We refer to this problem as extended gaze following. The contributions of the paper are the followings. First, we propose a novel spatial representation of the gaze directions adopting a top-view perspective. Second, we develop several convolutional encoder/decoder networks to predict object locations and compare them with heuristics and with classical learning-based approaches. Third, in order to train the proposed models, we generate a very large number of synthetic scenarios employing a probabilistic formulation. Finally, our methodology is empirically validated using a publicly available dataset.
AB - In this paper we address the problems of detecting objects of interest in a video and of estimating their locations, solely from the gaze directions of people present in the video. Objects can be indistinctly located inside or outside the camera field of view. We refer to this problem as extended gaze following. The contributions of the paper are the followings. First, we propose a novel spatial representation of the gaze directions adopting a top-view perspective. Second, we develop several convolutional encoder/decoder networks to predict object locations and compare them with heuristics and with classical learning-based approaches. Third, in order to train the proposed models, we generate a very large number of synthetic scenarios employing a probabilistic formulation. Finally, our methodology is empirically validated using a publicly available dataset.
UR - https://www.scopus.com/pages/publications/85070477597
U2 - 10.1109/FG.2019.8756555
DO - 10.1109/FG.2019.8756555
M3 - Conference contribution
AN - SCOPUS:85070477597
T3 - Proceedings - 14th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2019
BT - Proceedings - 14th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2019
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 14 May 2019 through 18 May 2019
ER -