ComputingVision ScienceAssistive TechnologyComputer VisionMobile ComputingGesture InteractionGesture RecognitionGesture-based InteractionMobile Human-computer InteractionMobile User ExperienceMultimodal InteractionGesture-based InterfacesHand GesturesInformation TransmissionReal-time Gesture RecognitionReal-time ProcessingSwipe GesturesTarget AcquisitionUser Study Evaluation
We present LensGesture, a pure software approach for augmenting mobile interactions with back-of-device finger gestures. LensGesture detects full and partial occlusion as well as the dynamic swiping of fingers on the camera lens by analyzing image sequences captured by the built-in camera in real time. We report the feasibility and implementation of LensGesture as well as newly supported interactions. Through offline benchmarking and a 16-subject user study, we found that 1) LensGesture is easy to learn, intuitive to use, and can serve as an effective supplemental input channel for today's smartphones; 2) LensGesture can be detected reliably in real time; 3) LensGesture based target acquisition conforms to Fitts' Law and the information transmission rate is 0.53 bits/sec; and 4) LensGesture applications can improve the usability and the performance of existing mobile interfaces.
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