Probabilistic visual recognition of artificial landmarks for simultaneous localization and mapping

Probabilistic robotics most often applied to the problem of simultaneous localisation and mapping (SLAM), requires measures of uncertainty to accompany observations of the environment. This paper describes how uncertainty can be characterised for a vision system that locates coloured landmarks in a typical laboratory environment. The paper describes a model of the uncertainty in segmentation, the internal cameral model and the mounting of the camera on the robot. It explains the implementation of the system on a laboratory robot, and provides experimental results that show the coherence of the uncertainty model.

Guidelines for filming digital camera video clips for the assessment of gait and movement disorders by teleneurology

Digital still cameras capable of filming short video clips are readily available, but the quality of these recordings for telemedicine has not been reported. We performed a blinded study using four commonly available digital cameras. A simulated patient with a hemiplegic gait pattern was filmed by the same videographer in an identical, brightly lit indoor setting. Six neurologists viewed the blinded video clips on their PC and comparisons were made between cameras, between video clips recorded with and without a tripod, and between video clips filmed on high- or low-quality settings. Use of a tripod had a smaller effect than expected, while images taken on a high-quality setting were strongly preferred to those taken on a low-quality setting. Although there was some variability in video quality between selected cameras, all were of sufficient quality to identify physical signs such as gait and tremor. Adequate-quality video clips of movement disorders can be produced with low-cost cameras and transmitted by email for teleneurology purposes.