Abstract
We propose a method for visualizing where an observer’s gaze focuses on a subject in a still image using a neutral human body model. Generally, two-dimensional (2D) heatmaps are superimposed on still images to visualize an observer’s gaze distribution, which indicates where an observer looks when observing a subject. To investigate gaze distributions, eye-tracking researchers need a method to directly compare the 2D heatmaps because body pose and shape differ among subjects. Thus, a comparison of the gaze distributions using the 2D heatmaps is time-consuming if there is no acceptable method to handle the body pose and shape variations. Instead, our visualization method superimposes a three-dimensional (3D) heatmap representing the gaze distribution on the surface of a neutral human body, which has a fixed pose and shape for all subjects to visualize the locations at which an observer’s gaze focuses. Experimental results show that our visualization method allows eye-tracking researchers to compare gaze distributions more directly than the conventional visualization method using 2D heatmaps on still images.
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Choutas, V., Müller, L., Huang, C.P., Tang, S., Tzionas, D., Black, M.J.: Accurate 3D body shape regression using metric and semantic attributes. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 2718–2728 (2022)
Georgios, P., et al.: Expressive body capture: 3D hands, face, and body from a single image. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 10975–10985 (2019)
Güler, R., Neverova, N., Kokkinos, I.: DensePose: dense human pose estimation in the wild. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 7297–7306 (2018)
Irvine, K.R., McCarty, K., Pollet, T.V., Cornelissen, K.K., Tovée, M.J., Cornelissen, P.L.: The visual cues that drive the self-assessment of body size: dissociation between fixation patterns and the key areas of the body for accurate judgement. Body Image 29, 31–46 (2019)
Matthew, M., Mahmood, N., Romero, J., Pons-Moll, G., Black, M.: SMPL: a skinned multi-person linear model. ACM Trans. Graph. 34(6), 1–16 (2015)
Nummenmaa, L., Jari, H., Santtila, P., Hyönä, J.: Gender and visibility of sexual cues influence eye movements while viewing faces and bodies. Arch. Sex. Behav. 41(6), 1439–1451 (2012)
Osman, A.A.A., Bolkart, T., Tzionas, D., Black, M.J.: SUPR: a sparse unified part-based human representation. In: Proceedings of European Conference on Computer Vision, pp. 1–18 (2022)
Piers, C., Peter, H., Kiviniemi, V., Hannah, G., Martin, T.: Patterns of eye movements when male and female observers judge female attractiveness, body fat and waist-to-hip ratio. Evol. Hum. Behav. 30(6), 417–428 (2009)
Takahashi, R., Suzuki, H., Chew, J., Ohtake, Y., Nagai, Y., Ohtomi, K.: A system for three-dimensional gaze fixation analysis using eye tracking glasses. J. Comput. Des. Eng. 5(4), 449–457 (2017)
Wang, X., Lindlbauer, D., Lessig, C., Maertens, M., Alexa, M.: Measuring the visual salience of 3D printed objects. IEEE Comput. Graphics Appl. 36(4), 46–55 (2016)
Xiu, Y., Yang, J., Tzionas, D., Black, M.J.: ICON: implicit clothed humans obtained from normals. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 13296–13306 (2022)
Zhang, H., et al.: PyMAF: 3D human pose and shape regression with pyramidal mesh alignment feedback loop. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 11446–11456 (2021)
Acknowledgment
This work was partially supported by JSPS KAKENHI Grant No. JP23K11145. We would like to thank Mr. Ken Kinoshita for his cooperation in our evaluation and data collection.
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Inoue, M., Iwasaki, F., Nishiyama, M., Iwai, Y. (2023). Heatmap Overlay Using Neutral Body Model for Visualizing the Measured Gaze Distributions of Observers. In: Lu, H., Blumenstein, M., Cho, SB., Liu, CL., Yagi, Y., Kamiya, T. (eds) Pattern Recognition. ACPR 2023. Lecture Notes in Computer Science, vol 14407. Springer, Cham. https://doi.org/10.1007/978-3-031-47637-2_8
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