GroupTogether is a system that explores cross-device interaction using two sociological constructs. First, Fformations concern the distance and relative body orientation among multiple users, which indicate when and how people position themselves as a group. Second, micromobility describes how people orient and tilt devices towards one another to promote fine-grained sharing during co-present collaboration. We sense these constructs using: (a) a pair of overhead Kinect depth cameras to sense small groups of people, (b) low-power 8GHz band radio modules to establish the identity, presence, and coarse-grained relative locations of devices, and (c) accelerometers to detect tilting of slate devices. The resulting system supports fluid, minimally disruptive techniques for co-located collaboration by leveraging the proxemics of people as well as the proxemics of devices.

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Abstract:The ability to monitor the respiratory rate, one of the vital signs, is extremely important for the medical treatment, healthcare and fitness sectors. In many situations, mobile methods, which allow users to undertake everyday activities, are required. However, current monitoring systems can be obtrusive, requiring users to wear respiration belts or nasal probes. Alternatively, contactless digital image sensor based remote-photoplethysmography (PPG) can be used. However, remote PPG requires an ambient source of light, and does not work properly in dark places or under varying lighting conditions. Recent advances in thermographic systems have shrunk their size, weight and cost, to the point where it is possible to create smart-phone based respiration rate monitoring devices that are not affected by lighting conditions. However, mobile thermal imaging is challenged in scenes with high thermal dynamic ranges (e.g. due to the different environmental temperature distributions indoors and outdoors). This challenge is further amplified by general problems such as motion artifacts and low spatial resolution, leading to unreliable breathing signals. In this paper, we propose a novel and robust approach for respiration tracking which compensates for the negative effects of variations in the ambient temperature and motion artifacts and can accurately extract breathing rates in highly dynamic thermal scenes. The approach is based on tracking the nostril of the user and using local temperature variations to infer inhalation and exhalation cycles. It has three main contributions. The first is a novel Optimal Quantization technique which adaptively constructs a color mapping of absolute temperature to improve segmentation, classification and tracking. The second is the Thermal Gradient Flow method that computes thermal gradient magnitude maps to enhance the accuracy of the nostril region tracking. Finally, we introduce the Thermal Voxel method to increase the reliability of the captured respiration signals compared to the traditional averaging method. We demonstrate the extreme robustness of our system to track the nostril-region and measure the respiratory rate by evaluating it during controlled respiration exercises in high thermal dynamic scenes (e.g. strong correlation (r = 0.9987) with the ground truth from the respiration-belt sensor). We also demonstrate how our algorithm outperformed standard algorithms in settings with different amounts of environmental thermal changes and human motion. We open the tracked ROI sequences of the datasets collected for these studies (i.e. under both controlled and unconstrained real-world settings) to the community to foster work in this area.

Toolkit research plays an important role in the field of HCI, as it can heavily influence both the design and implementation of interactive systems. For publication, the HCI community typically expects toolkit research to include an evaluation component. The problem is that toolkit evaluation is challenging, as it is often unclear what 'evaluating' a toolkit means and what methods are appropriate. To address this problem, we analyzed 68 published toolkit papers. From our analysis, we provide an overview of, reflection on, and discussion of evaluation methods for toolkit contributions. We identify and discuss the value of four toolkit evaluation strategies, including the associated techniques that each employs. We offer a categorization of evaluation strategies for toolkit researchers, along with a discussion of the value, potential limitations, and trade-offs associated with each strategy.