Massachusetts Mercury, 10 June 1800 (vol. 15, no. 46) - Newspaper

Volume 15 no. 46 of the Massachusetts Mercury dated 10 June, 1800.

Real-Time Automatic Object Classification and Tracking using Genetic Programming and NVIDIA R CUDA TM

Genetic Programming (GP) is a widely used methodology for solving various computational problems. GP's problem solving ability is usually hindered by its long execution times. In this thesis, GP is applied toward real-time computer vision. In particular, object classification and tracking using a parallel GP system is discussed. First, a study of suitable GP languages for object classification is presented. Two main GP approaches for visual pattern classification, namely the block-classifiers and the pixel-classifiers, were studied. Results showed that the pixel-classifiers generally performed better. Using these results, a suitable language was selected for the real-time implementation. Synthetic video data was used in the experiments. The goal of the experiments was to evolve a unique classifier for each texture pattern that existed in the video. The experiments revealed that the system was capable of correctly tracking the textures in the video. The performance of the system was on-par with real-time requirements.

HG 46.40-46.50

Brown sediment with areas of clay rich material (darker brown). Clasts range from small to large in size. Clast shape ranges from angular to rounded. Rotation structures and necking structures were abundant in this sample. Some lineations and grain stacking can also be seen throughout the sample.