Using Image Processing Methods to Improve the Detection of Buried Explosive Threats in GPR Data

Current state of the art techniques for landmine detection in ground penetrating radar (GPR) utilize statistical methods to identify characteristics of a landmine response. This research makes use of 2-D slices of data in which subsurface landmine responses have hyperbolic shapes. Various methods from the field of visual image processing are adapted to the 2-D GPR data, producing superior landmine detection results. This research goes on to develop a physics-based GPR augmentation method motivated by current advances in visual object detection. This GPR specific augmentation is used to mitigate issues caused by insufficient training sets. This work shows that augmentation improves detection performance under training conditions that are normally very difficult. Finally, this work introduces the use of convolutional neural networks as a method to learn feature extraction parameters. These learned convolutional features outperform hand-designed features in GPR detection tasks. This work presents a number of methods, both borrowed from and motivated by the substantial work in visual image processing. The methods developed and presented in this work show an improvement in overall detection performance and introduce a method to improve the robustness of statistical classification.

Exploring the effects of image persistence in low frame rate virtual environments

© 2015 IEEE.In virtual reality applications, there is an aim to provide real time graphics which run at high refresh rates. However, there are many situations in which this is not possible due to simulation or rendering issues. When running at low frame rates, several aspects of the user experience are affected. For example, each frame is displayed for an extended period of time, causing a high persistence image artifact. The effect of this artifact is that movement may lose continuity, and the image jumps from one frame to another. In this paper, we discuss our initial exploration of the effects of high persistence frames caused by low refresh rates and compare it to high frame rates and to a technique we developed to mitigate the effects of low frame rates. In this technique, the low frame rate simulation images are displayed with low persistence by blanking out the display during the extra time such image would be displayed. In order to isolate the visual effects, we constructed a simulator for low and high persistence displays that does not affect input latency. A controlled user study comparing the three conditions for the tasks of 3D selection and navigation was conducted. Results indicate that the low persistence display technique may not negatively impact user experience or performance as compared to the high persistence case. Directions for future work on the use of low persistence displays for low frame rate situations are discussed.

Frontal eye field neurons assess visual stability across saccades.

The image on the retina may move because the eyes move, or because something in the visual scene moves. The brain is not fooled by this ambiguity. Even as we make saccades, we are able to detect whether visual objects remain stable or move. Here we test whether this ability to assess visual stability across saccades is present at the single-neuron level in the frontal eye field (FEF), an area that receives both visual input and information about imminent saccades. Our hypothesis was that neurons in the FEF report whether a visual stimulus remains stable or moves as a saccade is made. Monkeys made saccades in the presence of a visual stimulus outside of the receptive field. In some trials, the stimulus remained stable, but in other trials, it moved during the saccade. In every trial, the stimulus occupied the center of the receptive field after the saccade, thus evoking a reafferent visual response. We found that many FEF neurons signaled, in the strength and timing of their reafferent response, whether the stimulus had remained stable or moved. Reafferent responses were tuned for the amount of stimulus translation, and, in accordance with human psychophysics, tuning was better (more prevalent, stronger, and quicker) for stimuli that moved perpendicular, rather than parallel, to the saccade. Tuning was sometimes present as well for nonspatial transaccadic changes (in color, size, or both). Our results indicate that FEF neurons evaluate visual stability during saccades and may be general purpose detectors of transaccadic visual change.