Ultrafast facial tracker using generic cameras with applications in intelligent lifestyle

Yung Hui Li; Yuan Ting Hu; Jethro Shen; Mihai Preda; Andrei Drexler; Carmen Sosoiu; Dragos Florin Stanculescu; Paul Liu; Joe Ye

doi:10.1007/978-3-319-39907-2_23

Ultrafast facial tracker using generic cameras with applications in intelligent lifestyle

Yung Hui Li, Yuan Ting Hu, Jethro Shen, Mihai Preda, Andrei Drexler, Carmen Sosoiu, Dragos Florin Stanculescu, Paul Liu, Joe Ye

Department of Computer Science and Information Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The core of Human-Computer Interaction (HCI) is to analyze and understand the user’s intension, which can be mostly manifested from the facial movement and expression of the user. Hence, the stage facial detection and tracking is extremely important in an user-friendly interface between human and computer. In ULSee, we developed an ultrafast markerless facial tracking system which is robust to variation in environmental lighting, pose and occlusion. It can be run at a speed of 10 ms/frame on an iPhone 6S system. With such accuracy and speed, it can be used to support many intelligent HCI applications. In this work, we envision an intelligent lifestyle in the future that can be built upon the basis of the ULSee’s ultrafast markerless facial tracker, ranging from virtual reality, augmented reality, real-time facial recognition and driver drowsiness detection. We believe, that through the joint force between ULSee’s world-class tracker and our clients, more user-awareness HCI application will be invented and a new lifestyle will arise.

Original language	English
Title of host publication	Virtual, Augmented and Mixed Reality - 8th International Conference, VAMR 2016 and Held as Part of HCI International 2016, Proceedings
Editors	Stephanie Lackey, Randall Shumaker
Publisher	Springer Verlag
Pages	243-254
Number of pages	12
ISBN (Print)	9783319399065
DOIs	https://doi.org/10.1007/978-3-319-39907-2_23
State	Published - 2016
Event	8th International Conference on Virtual, Augmented and Mixed Reality, VAMR 2016 and Held as Part of 18th International Conference on Human-Computer Interaction, HCI International 2016 - Toronto, Canada Duration: 17 Jul 2016 → 22 Jul 2016

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9740
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	8th International Conference on Virtual, Augmented and Mixed Reality, VAMR 2016 and Held as Part of 18th International Conference on Human-Computer Interaction, HCI International 2016
Country/Territory	Canada
City	Toronto
Period	17/07/16 → 22/07/16

Keywords

Driver
Drowsiness detection
Facial recognition
Markerless facial tracking
Real-time avatar animation

Access to Document

10.1007/978-3-319-39907-2_23

Cite this

Li, Y. H., Hu, Y. T., Shen, J., Preda, M., Drexler, A., Sosoiu, C., Stanculescu, D. F., Liu, P., & Ye, J. (2016). Ultrafast facial tracker using generic cameras with applications in intelligent lifestyle. In S. Lackey, & R. Shumaker (Eds.), Virtual, Augmented and Mixed Reality - 8th International Conference, VAMR 2016 and Held as Part of HCI International 2016, Proceedings (pp. 243-254). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9740). Springer Verlag. https://doi.org/10.1007/978-3-319-39907-2_23

Li, Yung Hui ; Hu, Yuan Ting ; Shen, Jethro et al. / Ultrafast facial tracker using generic cameras with applications in intelligent lifestyle. Virtual, Augmented and Mixed Reality - 8th International Conference, VAMR 2016 and Held as Part of HCI International 2016, Proceedings. editor / Stephanie Lackey ; Randall Shumaker. Springer Verlag, 2016. pp. 243-254 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Ultrafast facial tracker using generic cameras with applications in intelligent lifestyle",

abstract = "The core of Human-Computer Interaction (HCI) is to analyze and understand the user{\textquoteright}s intension, which can be mostly manifested from the facial movement and expression of the user. Hence, the stage facial detection and tracking is extremely important in an user-friendly interface between human and computer. In ULSee, we developed an ultrafast markerless facial tracking system which is robust to variation in environmental lighting, pose and occlusion. It can be run at a speed of 10 ms/frame on an iPhone 6S system. With such accuracy and speed, it can be used to support many intelligent HCI applications. In this work, we envision an intelligent lifestyle in the future that can be built upon the basis of the ULSee{\textquoteright}s ultrafast markerless facial tracker, ranging from virtual reality, augmented reality, real-time facial recognition and driver drowsiness detection. We believe, that through the joint force between ULSee{\textquoteright}s world-class tracker and our clients, more user-awareness HCI application will be invented and a new lifestyle will arise.",

keywords = "Driver, Drowsiness detection, Facial recognition, Markerless facial tracking, Real-time avatar animation",

author = "Li, {Yung Hui} and Hu, {Yuan Ting} and Jethro Shen and Mihai Preda and Andrei Drexler and Carmen Sosoiu and Stanculescu, {Dragos Florin} and Paul Liu and Joe Ye",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.; 8th International Conference on Virtual, Augmented and Mixed Reality, VAMR 2016 and Held as Part of 18th International Conference on Human-Computer Interaction, HCI International 2016 ; Conference date: 17-07-2016 Through 22-07-2016",

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Li, YH, Hu, YT, Shen, J, Preda, M, Drexler, A, Sosoiu, C, Stanculescu, DF, Liu, P & Ye, J 2016, Ultrafast facial tracker using generic cameras with applications in intelligent lifestyle. in S Lackey & R Shumaker (eds), Virtual, Augmented and Mixed Reality - 8th International Conference, VAMR 2016 and Held as Part of HCI International 2016, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9740, Springer Verlag, pp. 243-254, 8th International Conference on Virtual, Augmented and Mixed Reality, VAMR 2016 and Held as Part of 18th International Conference on Human-Computer Interaction, HCI International 2016, Toronto, Canada, 17/07/16. https://doi.org/10.1007/978-3-319-39907-2_23

Ultrafast facial tracker using generic cameras with applications in intelligent lifestyle. / Li, Yung Hui; Hu, Yuan Ting; Shen, Jethro et al.
Virtual, Augmented and Mixed Reality - 8th International Conference, VAMR 2016 and Held as Part of HCI International 2016, Proceedings. ed. / Stephanie Lackey; Randall Shumaker. Springer Verlag, 2016. p. 243-254 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9740).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Hu, Yuan Ting

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AU - Preda, Mihai

AU - Drexler, Andrei

AU - Sosoiu, Carmen

AU - Stanculescu, Dragos Florin

AU - Liu, Paul

AU - Ye, Joe

N1 - Publisher Copyright: © Springer International Publishing Switzerland 2016.

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N2 - The core of Human-Computer Interaction (HCI) is to analyze and understand the user’s intension, which can be mostly manifested from the facial movement and expression of the user. Hence, the stage facial detection and tracking is extremely important in an user-friendly interface between human and computer. In ULSee, we developed an ultrafast markerless facial tracking system which is robust to variation in environmental lighting, pose and occlusion. It can be run at a speed of 10 ms/frame on an iPhone 6S system. With such accuracy and speed, it can be used to support many intelligent HCI applications. In this work, we envision an intelligent lifestyle in the future that can be built upon the basis of the ULSee’s ultrafast markerless facial tracker, ranging from virtual reality, augmented reality, real-time facial recognition and driver drowsiness detection. We believe, that through the joint force between ULSee’s world-class tracker and our clients, more user-awareness HCI application will be invented and a new lifestyle will arise.

AB - The core of Human-Computer Interaction (HCI) is to analyze and understand the user’s intension, which can be mostly manifested from the facial movement and expression of the user. Hence, the stage facial detection and tracking is extremely important in an user-friendly interface between human and computer. In ULSee, we developed an ultrafast markerless facial tracking system which is robust to variation in environmental lighting, pose and occlusion. It can be run at a speed of 10 ms/frame on an iPhone 6S system. With such accuracy and speed, it can be used to support many intelligent HCI applications. In this work, we envision an intelligent lifestyle in the future that can be built upon the basis of the ULSee’s ultrafast markerless facial tracker, ranging from virtual reality, augmented reality, real-time facial recognition and driver drowsiness detection. We believe, that through the joint force between ULSee’s world-class tracker and our clients, more user-awareness HCI application will be invented and a new lifestyle will arise.

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KW - Real-time avatar animation

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Li YH, Hu YT, Shen J, Preda M, Drexler A, Sosoiu C et al. Ultrafast facial tracker using generic cameras with applications in intelligent lifestyle. In Lackey S, Shumaker R, editors, Virtual, Augmented and Mixed Reality - 8th International Conference, VAMR 2016 and Held as Part of HCI International 2016, Proceedings. Springer Verlag. 2016. p. 243-254. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-39907-2_23

Ultrafast facial tracker using generic cameras with applications in intelligent lifestyle

Abstract

Publication series

Conference

Keywords

Access to Document

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