Access to non-verbal cues in social interactions is vital for people with visual impairment. It has been shown that non-verbal cues such as eye contact, number of people, their names and positions are helpful for individuals who are blind. While there is an increasing interest in developing systems to provide these cues less emphasis has been put in evaluating its impact on the visually impaired users. In this paper, we provide this analysis by conducting a user study with 12 visually impaired participants in a typical social interaction setting. We design a real time multimodal system that provides such non-verbal cues via audio and haptic interfaces. The study shows that such systems are generally perceived as useful in social interaction and brings forward some concerns that are not being addressed in its usability aspects. The study provides important insight about developing such technology for this significant part of society.

The current COVID-19 pandemic is having a major impact on our daily lives. Social distancing is one of the measures that has been implemented with the aim of slowing the spread of the disease, but it is difficult for blind people to comply with this. In this paper, we present a system that helps blind people to maintain physical distance to other persons using a combination of RGB and depth cameras. We use a real-time semantic segmentation algorithm on the RGB camera to detect where persons are and use the depth camera to assess the distance to them; then, we provide audio feedback through bone-conducting headphones if a person is closer than 1.5 m. Our system warns the user only if persons are nearby but does not react to non-person objects such as walls, trees or doors; thus, it is not intrusive, and it is possible to use it in combination with other assistive devices. We have tested our prototype system on one blind and four blindfolded persons, and found that the system is precise, easy to use, and amounts to low cognitive load.

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Abstract. We present a computer vision system that helps blind people find lost objects. To this end, we combine color-and SIFT-based object detection with sonification to guide the hand of the user towards potential target object locations. This way, we are able to guide the user's attention and effectively reduce the space in the environment that needs to be explored. We verified the suitability of the proposed system in a user study.

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