Detection of pedestrian crossing in image-based blind aid devices
A new method to effectively detect pedestrian crossing in the image-based blind aid devices is proposed.Candidate regions of a crossing are selected by careful evaluation of the "bipolarity" which represent the gray level contrast in an image,and the noise of bipolarity image is eliminated by using morphology processing approaches.According to the corresponding relationships between an image and its Radon transform result,pedestrian crossing features,such as number and length of pedestrian crossing stripes,angles in vision field,are extracted in transform domain.This algorithm is proved to be effective with 96.2% accuracy under the test of 54 real crossing images.
In hospitals, offices and other settings, professionals face the challenge of accessing and sharing sensitive content in public areas. As tablets become increasingly adopted in work environments, it is important to explore ways to support privacy that are appropriate for tablet use in dynamic, mobile workflows. In this research we consider how spatial information can be utilized to support both individual and collaborative work in a natural way while respecting data privacy. We present a proof-of-concept implementation of a proximity-aware tablet, and a range of privacy notification and control mechanisms designed for such a tablet. Results from a user study support the idea that interpersonal distance and orientation can be used to mediate privacy management for tablet interfaces. Selecting a specific design for privacy threat notification and response is highly context-dependent-for example, in health care the first priority is to not impede the fluid exchange of information.