μ-MAR: Multiplane 3D Marker based Registration for depth-sensing cameras

Many applications including object reconstruction, robot guidance, and. scene mapping require the registration of multiple views from a scene to generate a complete geometric and appearance model of it. In real situations, transformations between views are unknown and it is necessary to apply expert inference to estimate them. In the last few years, the emergence of low-cost depth-sensing cameras has strengthened the research on this topic, motivating a plethora of new applications. Although they have enough resolution and accuracy for many applications, some situations may not be solved with general state-of-the-art registration methods due to the signal-to-noise ratio (SNR) and the resolution of the data provided. The problem of working with low SNR data, in general terms, may appear in any 3D system, then it is necessary to propose novel solutions in this aspect. In this paper, we propose a method, μ-MAR, able to both coarse and fine register sets of 3D points provided by low-cost depth-sensing cameras, despite it is not restricted to these sensors, into a common coordinate system. The method is able to overcome the noisy data problem by means of using a model-based solution of multiplane registration. Specifically, it iteratively registers 3D markers composed by multiple planes extracted from points of multiple views of the scene. As the markers and the object of interest are static in the scenario, the transformations obtained for the markers are applied to the object in order to reconstruct it. Experiments have been performed using synthetic and real data. The synthetic data allows a qualitative and quantitative evaluation by means of visual inspection and Hausdorff distance respectively. The real data experiments show the performance of the proposal using data acquired by a Primesense Carmine RGB-D sensor. The method has been compared to several state-of-the-art methods. The results show the good performance of the μ-MAR to register objects with high accuracy in presence of noisy data outperforming the existing methods.

Interpersonal relations and nurses' job satisfaction through knowledge and usage of relational skills

Background/rationale: Many interpersonal labor disputes stem from the lack of communication skills and the relational problems in the interactions between health professionals. Aims/methods: A qualitative study was conducted in a Spanish hospital in order to get to know how the communicative interaction between hospital nurses is like in relation to the nurses' interpersonal interaction and communication skills developed in their working relationships. Twenty-one hospital nurses between 29 and 55 years old, working in different wards, were interviewed. Open-ended interview discourses were transcribed verbatim and analyzed using qualitative content analysis. Results: The following four key themes were analyzed: communication and sender; communication and awareness of who has the problem; non-verbal communication; communication and recipient. Conclusion: The results of this study highlight the need to broaden nurses' relational–communication skills in order to increase job satisfaction.