Paper
13 April 2018 Face landmark point tracking using LK pyramid optical flow
Gang Zhang, Sikan Tang, Jiaquan Li
Author Affiliations +
Proceedings Volume 10696, Tenth International Conference on Machine Vision (ICMV 2017); 106962B (2018) https://doi.org/10.1117/12.2311458
Event: Tenth International Conference on Machine Vision, 2017, Vienna, Austria
Abstract
LK pyramid optical flow is an effective method to implement object tracking in a video. It is used for face landmark point tracking in a video in the paper. The landmark points, i.e. outer corner of left eye, inner corner of left eye, inner corner of right eye, outer corner of right eye, tip of a nose, left corner of mouth, right corner of mouth, are considered. It is in the first frame that the landmark points are marked by hand. For subsequent frames, performance of tracking is analyzed. Two kinds of conditions are considered, i.e. single factors such as normalized case, pose variation and slowly moving, expression variation, illumination variation, occlusion, front face and rapidly moving, pose face and rapidly moving, and combination of the factors such as pose and illumination variation, pose and expression variation, pose variation and occlusion, illumination and expression variation, expression variation and occlusion. Global measures and local ones are introduced to evaluate performance of tracking under different factors or combination of the factors. The global measures contain the number of images aligned successfully, average alignment error, the number of images aligned before failure, and the local ones contain the number of images aligned successfully for components of a face, average alignment error for the components. To testify performance of tracking for face landmark points under different cases, tests are carried out for image sequences gathered by us. Results show that the LK pyramid optical flow method can implement face landmark point tracking under normalized case, expression variation, illumination variation which does not affect facial details, pose variation, and that different factors or combination of the factors have different effect on performance of alignment for different landmark points.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Gang Zhang, Sikan Tang, and Jiaquan Li "Face landmark point tracking using LK pyramid optical flow", Proc. SPIE 10696, Tenth International Conference on Machine Vision (ICMV 2017), 106962B (13 April 2018); https://doi.org/10.1117/12.2311458
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Cited by 2 scholarly publications.
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KEYWORDS
Optical flow

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