Imaging of the optic disc and retinal nerve fiber layer: the effects of age, optic disc area, refractive error, and gender.

We cross-sectionally examined the relationship between age, optic disc area, refraction, and gender and optic disc topography and retinal nerve fiber layer (RNFL) measurements, using optical imaging techniques. One eye from each of 155 Caucasian subjects (age range 23.0-80.8 y) without ocular pathology was included. Measurements were obtained by using the Heidelberg Retina Tomography (HRT), the GDx Nerve Fiber Analyzer, and the Optical Coherence Tomograph (OCT). The effects of age were small (R2 < 17%) and were limited to specific HRT, GDx, and OCT parameters. Disc area was significantly associated with most HRT parameters and isolated GDx and OCT parameters. Refraction and gender were not significantly associated with any optic disc or RNFL parameters. Although effects of age on the optic disc and RNFL are small, they should be considered in monitoring ocular disease. Optic disc area should be considered when cross-sectionally evaluating disc topography and, to a lesser extent, RNFL thickness.     

Kernel machines for current status data

Machine Learning - In survival analysis, estimating the failure time distribution is an important and difficult task, since usually the data is subject to censoring. Specifically, in this paper we...     

Photo Sequencing

A group of people taking pictures of a dynamic event with their mobile phones is a popular sight. The set of still images obtained this way is rich in dynamic content but lacks accurate temporal information. We propose a method for photo-sequencing—temporally ordering a set of still images taken asynchronously by a set of uncalibrated cameras. Photo-sequencing is an essential tool in analyzing (or visualizing) a dynamic scene captured by still images. The first step of the method detects sets of corresponding static and dynamic feature points across images. The static features are used to determine the epipolar geometry between pairs of images, and each dynamic feature votes for the temporal order of the images in which it appears. The partial orders provided by the dynamic features are not necessarily consistent, and we use rank aggregation to combine them into a globally consistent temporal order of images. We demonstrate successful photo-sequencing on several challenging collections of images taken using a number of mobile phones.     

Quantitative Characterization of Indentation Crack Path in a Cubic Zirconia-10 vol% Alumina Composite

Stereological measurements were performed to characterize the indentation crack path in a cubic zirconia-10 vol% alumina (c-ZrO₂-10 vol% Al₂O₃) composite. Cracks were generated using Vickers indentation, and the crack propagation behavior was characterized as a function of the indentation loading/unloading rates. Cracks that were produced by Vickers indentation formed at higher crack velocities as the loading/unloading rates increased. The amount of contact between the crack and the Al₂O₃ particles increased as the indentation rate decreased. The total number of crack-particle interactions per unit crack length also increased as the indentation rate decreased, because of an increase in the number of particles that were fractured per unit crack length, whereas the number of particles that were debonded remained relatively constant as the indentation rate changed. These results suggest that residual thermal mismatch stresses have predominant control of the crack path at lower crack velocities (low indentation loading/unloading rate), whereas elastic mismatch stresses predominate at higher crack velocities (high indentation loading/unloading rate).     

High-throughput drilling of titanium alloys

Experiments of high-throughput drilling of Ti–6Al–4V at 183 m/min cutting speed and 156 mm³/s material removal rate (MRR) using a 4 mm diameter WC–Co spiral point drill were conducted. The tool material and geometry and drilling process parameters, including cutting speed, feed, and fluid supply, were studied to evaluate the effect on drill life, thrust force, torque, energy, and burr formation. The tool wear mechanism, hole surface roughness, and chip light emission and morphology for high-throughput drilling were investigated. Supplying the cutting fluid via through-the-drill holes has proven to be a critical factor for drill life, which can be increased by 10 times compared to that of dry drilling at 183 m/min cutting speed and 0.051 mm/rev feed. Under the same MRR of 156 mm³/s with a doubled feed of 0.102 mm/rev (91 m/min cutting speed), over 200 holes can be drilled. The balance of cutting speed and feed is essential to achieve long drill life and good hole surface roughness. This study demonstrates that, using proper drilling process parameters, spiral point drill geometry, and fine-grained WC–Co tool material, the high-throughput drilling of Ti alloy is technically feasible.     

Self adaptive animation based on user perspective

In this paper we present a new character animation technique in which the animation adapts itself based on the change in the user’s perspective, so that when the user moves and their point of viewing the animation changes, then the character animation adapts itself in response to that change. The resulting animation, generated in real-time, is a blend of key animations provided a priori by the animator. The blending is done with the help of efficient dual-quaternion transformation blending. The user’s point of view is tracked using either computer vision techniques or a simple user-controlled input modality, such as mouse-based input. This tracked point of view is then used to suitably select the blend of animations. We show a way to author and use such animations in both virtual as well as augmented reality scenarios and demonstrate that it significantly heightens the sense of presence for the users when they interact with such self adaptive animations of virtual characters.     

Tracking in a Dense Crowd Using Multiple Cameras

Tracking people in a dense crowd is a challenging problem for a single camera tracker due to occlusions and extensive motion that make human segmentation difficult. In this paper we suggest a method for simultaneously tracking all the people in a densely crowded scene using a set of cameras with overlapping fields of view. To overcome occlusions, the cameras are placed at a high elevation and only people’s heads are tracked. Head detection is still difficult since each foreground region may consist of multiple subjects. By combining data from several views, height information is extracted and used for head segmentation. The head tops, which are regarded as 2D patches at various heights, are detected by applying intensity correlation to aligned frames from the different cameras. The detected head tops are then tracked using common assumptions on motion direction and velocity. The method was tested on sequences in indoor and outdoor environments under challenging illumination conditions. It was successful in tracking up to 21 people walking in a small area (2.5 people per m²), in spite of severe and persistent occlusions.     

Exhaustive and heuristic search approaches for learning a software defect prediction model

In this paper, we propose a software defect prediction model learning problem (SDPMLP) where a classification model selects appropriate relevant inputs, from a set of all available inputs, and learns the classification function. We show that the SDPMLP is a combinatorial optimization problem with factorial complexity, and propose two hybrid exhaustive search and probabilistic neural network (PNN), and simulated annealing (SA) and PNN procedures to solve it. For small size SDPMLP, exhaustive search PNN works well and provides an (all) optimal solution(s). However, for large size SDPMLP, the use of exhaustive search PNN approach is not pragmatic and only the SA–PNN allows us to solve the SDPMLP in a practical time limit. We compare the performance of our hybrid approaches with traditional classification algorithms and find that our hybrid approaches perform better than traditional classification algorithms.     

3D Shape Recovery of Smooth Surfaces: Dropping the Fixed-Viewpoint Assumption

We present a new method for recovering the 3D shape of a featureless smooth surface from three or more calibrated images illuminated by different light sources (three of them are independent). This method is unique in its ability to handle images taken from unconstrained perspective viewpoints and unconstrained illumination directions. The correspondence between such images is hard to compute and no other known method can handle this problem locally from a small number of images. Our method combines geometric and photometric information in order to recover dense correspondence between the images and accurately computes the 3D shape. Only a single pass starting at one point and local computation are used. This is in contrast to methods that use the occluding contours recovered from many images to initialize and constrain an optimization process. The output of our method can be used to initialize such processes. In the special case of fixed viewpoint, the proposed method becomes a new perspective photometric stereo algorithm. Nevertheless, the introduction of the multiview setup, self-occlusions, and regions close to the occluding boundaries are better handled, and the method is more robust to noise than photometric stereo. Experimental results are presented for simulated and real images.