Efficient Human Pose Estimation with Image-dependent Interactions

Human pose estimation from 2D images is one of the most challenging and computationally-demanding problems in computer vision. Standard models such as Pictorial Structures consider interactions between kinematically connected joints or limbs, leading to inference cost that is quadratic in the number of pixels. As a result, researchers and practitioners have restricted themselves to simple models which only measure the quality of limb-pair possibilities by their 2D geometric plausibility. In this talk, we propose novel methods which allow for efficient inference in richer models with data-dependent interactions. First, we introduce structured prediction cascades, a structured analog of binary cascaded classifiers, which learn to focus computational effort where it is needed, filtering out many states cheaply while ensuring the correct output is unfiltered. Second, we propose a way to decompose models of human pose with cyclic dependencies into a collection of tree models, and provide novel methods to impose model agreement. Finally, we develop a local linear approach that learns bases centered around modes in the training data, giving us image-dependent local models which are fast and accurate. These techniques allow for sparse and efficient inference on the order of minutes or seconds per image. As a result, we can afford to model pairwise interaction potentials much more richly with data-dependent features such as contour continuity, segmentation alignment, color consistency, optical flow and multiple modes. We show empirically that these richer models are worthwhile, obtaining significantly more accurate pose estimation on popular datasets

Projected Augmented Reality to Drive Osteotomy Surgery: Implementation and Comparison With Video See-Through Technology

In recent years, the spreading of visual augmented reality as an effective tool in image-guided surgery, has stimulated the research community to investigate the use of commercial augmented reality headsets a broad range of potential applications. This aroused enthusiasm among clinicians for the potential of augmented reality, but also revealed some technological and human-factor limitations that still hinder its routine adoption in the operating room. In this work, we propose an alternative to head-mounted displays, based on projected augmented reality. Projected augmented reality completely preserves the surgeon’s natural view of the operating field, because it requires no perspective conversion and/or optical mediation. We selected a cranio-maxillofacial surgery application as a benchmark to test the proposed system and compare its accuracy with the one obtained with a video see-through system. The augmented reality overlay accuracy was evaluated by measuring the distance between a virtual osteotomy line and its real counterpart. The experimental tests showed that the accuracy of the two augmented reality modes is similar, with a median error discrepancy of about 0.3 mm for the projected augmented reality mode. Results suggest that projected augmented reality can be a valuable alternative to standard see-through head-mounted displays to support in-situ visualization of medical imaging data as surgical guidance

Robust Head Mounted Wearable Eye Tracking System for Dynamical Calibration

In this work, a new head mounted eye tracking system is presented. Based on computer vision techniques, the system integrates eye images and head movement, in real time, performing a robust gaze point tracking. Nystagmus movements due to vestibulo-ocular reflex are monitored and integrated. The system proposed here is a strongly improved version of a previous platform called HATCAM, which was robust against changes of illumination conditions. The new version, called HAT-Move, is equipped with accurate inertial motion unit to detect the head movement enabling eye gaze even in dynamical conditions. HAT-Move performance is investigated in a group of healthy subjects in both static and dynamic conditions, i.e. when head is kept still or free to move. Evaluation was performed in terms of amplitude of the angular error between the real coordinates of the fixed points and those computed by the system in two experimental setups, specifically, in laboratory settings and in a 3D virtual reality (VR) scenario. The achieved results showed that HAT-Move is able to achieve eye gaze angular error of about 1 degree along both horizontal and vertical direction

Aeronautical Engineering: A special bibliography with indexes, supplement 62

This bibliography lists 306 reports, articles, and other documents introduced into the NASA scientific and technical information system in September 1975

Ciclogénesis explosivas en el sector Euro-Atlántico: estudio de su dinámica a gran escala y variabilidad

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Ciencias Físicas, Departamento de Física de la Tierra, Astronomía y Astrofísica I (Geofísica y Meteorología) (Astronomía y Geodesia), leída el 27-11-2015.Depto. de Física de la Tierra y AstrofísicaFac. de Ciencias FísicasTRUEunpu