An Efficient Robust Eye Localization by Learning the Convolution Distribution Using Eye Template

Eye localization is a fundamental process in many facial analyses. In practical use, it is often challenged by illumination, head pose, facial expression, occlusion, and other factors. It remains great difficulty to achieve high accuracy with short prediction time and low training cost at the same time. This paper presents a novel eye localization approach which explores only one-layer convolution map by eye template using a BP network. Results showed that the proposed method is robust to handle many difficult situations. In experiments, accuracy of 98% and 96%, respectively, on the BioID and LFPW test sets could be achieved in 10 fps prediction rate with only 15-minute training cost. In comparison with other robust models, the proposed method could obtain similar best results with greatly reduced training time and high prediction speed

Application of Neural Networks for Intelligent Video Game Character Artificial Intelligences

Much of today’s gaming culture pushes for increased realism and believability. While these movements have led to much more realistic graphics, we also need to keep in mind the behavior of artificial intelligence characters also in the game. Neural Networks are complicated data structures that have shown potential to learn and interpret complex behavior. This research analyzes the application of neural network as primary controllers for video game characters’ artificial intelligence. The paper considers the existing artificial intelligence techniques, and the existing uses of neural networks. It then describes a project in which a video game was created to serve as a case study in analyzing neural network controlled game characters. The paper discusses the design of the game where the player communicates with an artificial intelligence astronaut. The way that the player phrases the messages he sends to the astronaut helps determine whether the astronaut survives. The paper then analyzes the effectiveness of the astronaut character in exhibiting intelligent behavior. It then discusses potential future work in better demonstrating effective neural network controlled artificial intelligences