ViRi: View It Right

Pan Hu, Guobin Shen, Liqun Li, and Donghuan Lu

Abstract

We present ViRi – an intriguing system that enables a user to enjoy a frontal view experience even when the user is actually at a slanted viewing angle. ViRi tries to restore the front-view effect by enhancing the normal content rendering process with an additional geometry correction stage. The necessary prerequisite is effectively and accurately estimating the actual viewing angle under natural viewing situations and under the constraints of the device's computational power and limited battery deposit.

We tackle the problem with face detection and augment the phone camera with a fisheye lens to expand its field of view so that the device can recognize its user even the phone is placed casually. We propose effective pre-processing techniques to ensure the applicability of face detection tools onto highly distorted fisheye images. To save energy, we leverage information from system states, employ multiple low power sensors to rule out unlikely viewing situations, and aggressively seek additional opportunities to maximally skip the face detection. For situations in which face detection is unavoidable, we design efficient prediction techniques to further speed up the face detection. The effectiveness of the proposed techniques have been confirmed through thorough evaluations. We have also built a straw man application to allow users to experience the intriguing effects of ViRi.

Details

Publication typeProceedings
PublisherACM International Conference in Mobile Systems, Applications, and Services (MobiSys)
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