Head Orientation Estimation from a Low-Resolution Far-Infrared Image Sequence

Taiyo Tamaki, Motoharu Sonogashira, Kazuya Kitano, Yuki Fujimura, Takuya Funatomi, Yasuhiro Mukaigawa, Yasutomo Kawanishi

Abstract: We propose a novel method for estimating head orientation from a low-resolution far-infrared (LFIR) image sequence captured by a 32 × 32 FIR sensor array. Estimating head orientation from LFIR images is challenging due to their inherent noise and limited resolution. Manually an-notating head orientation is also difficult, and no suitable dataset currently exists. We propose the LFIR2Head model, which leverages a multimodal-temporal framework for robust estimation. We also introduce the LFIR2Head dataset, which was created using an automatic annotation system. Extensive experiments demonstrate the accuracy of head orientation estimation with the proposed dataset. We con-firmed that head orientation can be estimated accurately from an LFIR image sequence.

External IDs:dblp:conf/avss/TamakiSKFFMK25