Face Tracking for Spatially Aware Mobile User Interfaces

Hannuksela, Jari; Sangi, Pekka; Turtinen, Markus; Heikkilä, Janne

doi:10.1007/978-3-540-69905-7_46

Cited by 10 publications

(13 citation statements)

References 14 publications

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“…In addition, as we focus on the interaction, we do not specifically look for a robust tracking under extreme or varying lighting conditions. Some clues on how to implement a robust face tracker can be found in [8], [14] and [27].…”

Section: Face Trackingmentioning

confidence: 99%

“…On mobile devices, most research focuses on defining efficient and robust algorithms [8] [14] for head tracking (with varying lighting conditions and low computational cost), but only a few use it for HCP. pCubee [31] is a device that arranges five small screens into a small box shape and combines it with HCP technique.…”

Section: Related Workmentioning

confidence: 99%

“…Since the seminal work of Rekimoto [25], there have been many systems that are based on motion sensors for enriching the interaction capacity of mobile devices. Amongst them, one relevant way to take advantage of the mobility is to use spatially aware displays [13] [14], which transform a position-tracked device into a window on a larger virtual workspace. By moving the device around, the user can access different parts of the workspace.…”

Section: Introductionmentioning

confidence: 99%

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Using the user's point of view for interaction on mobile devices

Francone

Nigay

2011

Proceedings of the 23rd Conference on l'Interaction Homme-Machine

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RESUMENous présentons une technique d'interaction pour dispositifs mobiles (smartphone et tablette) basée sur le suivi du visage de l'utilisateur. Cette technique définit de nouvelles possibilités pour l'interaction en entrée et en sortie sur dispositifs mobiles. En sortie, le suivi de la tête peut permettre de contrôler le point de vue sur une scène 3D affichée à l'écran (Head-Coupled Perspective, HCP). Cette technique améliore l'interaction en sortie en offrant la perception de la profondeur et en permettant la visualisation d'un espace de travail plus grand (fenêtre virtuelle). En entrée, le suivi des mouvements de la tête définit une nouvelle modalité d'interaction qui ne requiert pas d'autres capteurs que la caméra du téléphone ou de la tablette. Dans cet article, nous explicitons les possibilités interactionnelles offertes par le suivi de la tête de l'utilisateur sur téléphones ou tablettes, particulièrement adapté au caractère mobile des dispositifs visés. Nous focalisons ensuite sur l'interaction en sortie en présentant plusieurs applications du HCP et en décrivant les résultats d'une expérimentation qualitative sur téléphone et tablette. ABSTRACTWe study interaction modalities for mobile devices (smartphones and tablets) that rely on a camera-based head tracking. This technique defines new possibilities for input and output interaction. For output, by computing the position of the device according to the user's head, it is for example possible to realistically control the viewpoint on a 3D scene (Head-Coupled Perspective, HCP). This technique improves the output interaction bandwidth by enhancing the depth perception and by allowing the visualization of large workspaces (virtual window). For input, head movement can be used as a means of interacting with a mobile device. Moreover such an input modality does not require any additional sensor except the built-in front-facing camera. In this paper, we classify the interaction possibilities offered by head tracking on smartphones and tablets. We then focus on the output interaction by introducing several applications of HCP on both smartphones and tablets and by presenting the results of a qualitative user experiment.

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Section: Face Trackingmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Using the user's point of view for interaction on mobile devices

Francone

Nigay

2011

Proceedings of the 23rd Conference on l'Interaction Homme-Machine

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“…Hannuksela et al [8] presented a feature based head tracking method which can run in real-time on a resource limited mobile device.…”

Section: Fitzmaurice Et Al Described Rotating Usermentioning

confidence: 99%

iRotate

Cheng

Hsiao

Liu

et al. 2012

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

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We present iRotate, an approach to automatically rotate screens on mobile devices to match users' face orientation. Current approaches to automatic screen rotation are based on gravity and device orientation. Our survey of 513 users shows that 42% currently experience auto-rotation that leads to incorrect viewing orientation several times a week or more, and 24% find the problem to be very serious to extremely serious. iRotate augments gravity-based approach, and uses front cameras on mobile devices to detect users' faces and rotates screens accordingly. It requires no explicit user input and supports different user postures and device orientations. We have implemented an iRotate that works in real-time on iPhone and iPad, and we assess the accuracy and limitations of iRotate through a 20participant feasibility study.

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“…Interaction methods have been developed using the images captured by the camera as input primitive, mostly to detect the movement of the device [4,2]. In addition, the integration of front cameras opens the door to head-trackers interfaces (interaction with devices through head movements) [3,6] as used in commercial applications such as the Smart Screen Samsung Galaxy S4 that uses the front camera to detect the position of the face and eyes to perform functions like scroll within documents, screen rotation or pause video playback. Summarizing, previous works on head-tracker interfaces focused on the development of new access methods instead of analyzing the users performance.…”

Section: Introductionmentioning

confidence: 99%

Face Me! Head-Tracker Interface Evaluation on Mobile Devices

Roig-Maimó

Varona

Manresa-Yee

2015

Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems

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The integration of front cameras on mobile devices and the increase on processing capacity has opened the door to head-tracker interfaces on mobile devices. However, research mostly focus on the development of new interfaces and their integration into prototypes without analyzing human performance. In this work, we present a head-tracker interface for mobile devices and its evaluation from the point of view of Human-Computer Interaction. Nineteen participants performed position-select tasks using their nose's movement. User performance was measured with different device orientations and combining different gain and target width. Based on the obtained results, two design recommendations were made for those designers using the developed interface. In addition, we confirmed that device orientation, a particular feature for mobile devices that does not affect desktop computers, has no effect on the user's performance.

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Face Tracking for Spatially Aware Mobile User Interfaces

Cited by 10 publications

References 14 publications

Using the user's point of view for interaction on mobile devices

Using the user's point of view for interaction on mobile devices

iRotate

Face Me! Head-Tracker Interface Evaluation on Mobile Devices

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