MAM: Transfer learning for fully automatic video annotation and specialized detector creation

Wolfgang Fuhl, Nora Castner, Lin Zhuang, Markus Holzer, Wolfgang Rosenstiel, Enkelejda Kasneci

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

3 Zitate (Scopus)


Accurate point detection on image data is an important task for many applications, such as in robot perception, scene understanding, gaze point regression in eye tracking, head pose estimation, or object outline estimation. In addition, it can be beneficial for various object detection tasks where minimal bounding boxes are searched and the method can be applied to each corner. We propose a novel self training method, Multiple Annotation Maturation (MAM) that enables fully automatic labeling of large amounts of image data. Moreover, MAM produces detectors, which can be used online afterward. We evaluated our algorithm on data from different detection tasks for eye, pupil center (head mounted and remote), and eyelid outline point and compared the performance to the state-of-the-art. The evaluation was done on over 300,000 images, and our method shows outstanding adaptability and robustness. In addition, we contribute a new dataset with more than 16,200 accurate manually-labeled images from the remote eyelid, pupil center, and pupil outline detection. This dataset was recorded in a prototype car interior equipped with all standard tools, posing various challenges to object detection such as reflections, occlusion from steering wheel movement, or large head movements. The data set and library are available for download at

TitelComputer Vision – ECCV 2018 Workshops, Proceedings
Redakteure/-innenLaura Leal-Taixé, Stefan Roth
Herausgeber (Verlag)Springer Verlag
ISBN (Print)9783030110208
PublikationsstatusVeröffentlicht - 2019
Extern publiziertJa
Veranstaltung15th European Conference on Computer Vision, ECCV 2018 - Munich, Deutschland
Dauer: 8 Sept. 201814 Sept. 2018


NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Band11133 LNCS
ISSN (Print)0302-9743
ISSN (elektronisch)1611-3349


Konferenz15th European Conference on Computer Vision, ECCV 2018


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