Correction of geometric perceptual distortions in pictures
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
Squaring the Circles in Panoramas
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
A Generic Camera Model and Calibration Method for Conventional, Wide-Angle, and Fish-Eye Lenses
IEEE Transactions on Pattern Analysis and Machine Intelligence
EyePhone: activating mobile phones with your eyes
Proceedings of the second ACM SIGCOMM workshop on Networking, systems, and applications on mobile handhelds
LittleRock: Enabling Energy-Efficient Continuous Sensing on Mobile Phones
IEEE Pervasive Computing
EyeGuardian: a framework of eye tracking and blink detection for mobile device users
Proceedings of the Twelfth Workshop on Mobile Computing Systems & Applications
iRotate: automatic screen rotation based on face orientation
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Improving energy efficiency of personal sensing applications with heterogeneous multi-processors
Proceedings of the 2012 ACM Conference on Ubiquitous Computing
A reliable and accurate indoor localization method using phone inertial sensors
Proceedings of the 2012 ACM Conference on Ubiquitous Computing
Automatic exposure correction of consumer photographs
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part IV
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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.