Automated object identification and position estimation for airport lighting quality assessment

The development of an automated system for the quality assessment of aerodrome ground lighting (AGL), in accordance with associated standards and recommendations, is presented. The system is composed of an image sensor, placed inside the cockpit of an aircraft to record images of the AGL during a normal descent to an aerodrome. A model-based methodology is used to ascertain the optimum match between a template of the AGL and the actual image data in order to calculate the position and orientation of the camera at the instant the image was acquired. The camera position and orientation data are used along with the pixel grey level for each imaged luminaire, to estimate a value for the luminous intensity of a given luminaire. This can then be compared with the expected brightness for that luminaire to ensure it is operating to the required standards. As such, a metric for the quality of the AGL pattern is determined. Experiments on real image data is presented to demonstrate the application and effectiveness of the system.

Identification of tone duration, line length and letter position: An experimental approach to timing and working memory deficits in schizophrenia.

Patients with schizophrenia display numerous cognitive deficits, including problems in working memory, time estimation, and absolute identification of stimuli. Research in these fields has traditionally been conducted independently. We examined these cognitive processes using tasks that are structurally similar and that yield rich error data. Relative to healthy control participants (n = 20), patients with schizophrenia (n = 20) were impaired on a duration identification task and a probed-recall memory task but not on a line-length identification task. These findings do not support the notion of a global impairment in absolute identification in schizophrenia. However, the authors suggest that some aspect of temporal information processing is indeed disturbed in schizophrenia.

Rao-blackwellized particle filter for human appearance and position tracking

In human motion analysis, the joint estimation of appearance, body pose and location parameters is not always tractable due to its huge computational cost. In this paper, we propose a Rao-Blackwellized Particle Filter for addressing the problem of human pose estimation and tracking. The advantage of the proposed approach is that Rao-Blackwellization allows the state variables to be splitted into two sets, being one of them analytically calculated from the posterior probability of the remaining ones. This procedure reduces the dimensionality of the Particle Filter, thus requiring fewer particles to achieve a similar tracking performance. In this manner, location and size over the image are obtained stochastically using colour and motion clues, whereas body pose is solved analytically applying learned human Point Distribution Models.