Storage free terrain simulation

Landscape visualisation is the process of recreating a natural environment and displaying it in an interactive graphical simulation. To do this a terrain is displayed together with accompanying plant life and other objects. Present landscape visualisation software is capable in theory of displaying very detailed and large landscapes. The software is also in theory capable of simulating environments with thousands if not millions of individually structured plants. In practice though, the simulation of such landscapes requires such a large amount of storage space that it is not achievable on personal computers. Even storing small landscapes with a moderate amount plant life can be a major development problem. The extent of this problem is such that modem simulators almost always exhibit the following limitations. • When detailed landscapes are stored to the hard disk, the area of terrain covered is usually very small. • When large terrains are stored to the hard disk the detail used is usually low. • When detailed plants are used in a landscape only twenty or so plants are created and used over and over again in the landscape. This work is an original approach to solving the storage space problem that involves not storing any landscape data to the hard disk at all. In this solution, instead of the landscape simulator displaying a landscape that is stored on a hard disk, the landscape simulator displays a landscape that is randomly generated. The landscape is produced on a need-to know basis, the only landscape that exists in the simulator is the landscape that the user of the simulator can see. If the user\u27s position in the landscape alters then the newly visible areas of landscape are created, and the areas no longer visible are removed from the simulator entirely. Areas of landscape being visited for a second time are always re-created the same way as they were originally created

On the Recognition of Emotion from Physiological Data

This work encompasses several objectives, but is primarily concerned with an experiment where 33 participants were shown 32 slides in order to create ‗weakly induced emotions‘. Recordings of the participants‘ physiological state were taken as well as a self report of their emotional state. We then used an assortment of classifiers to predict emotional state from the recorded physiological signals, a process known as Physiological Pattern Recognition (PPR). We investigated techniques for recording, processing and extracting features from six different physiological signals: Electrocardiogram (ECG), Blood Volume Pulse (BVP), Galvanic Skin Response (GSR), Electromyography (EMG), for the corrugator muscle, skin temperature for the finger and respiratory rate. Improvements to the state of PPR emotion detection were made by allowing for 9 different weakly induced emotional states to be detected at nearly 65% accuracy. This is an improvement in the number of states readily detectable. The work presents many investigations into numerical feature extraction from physiological signals and has a chapter dedicated to collating and trialing facial electromyography techniques. There is also a hardware device we created to collect participant self reported emotional states which showed several improvements to experimental procedure

An approach to real-time plant creation

In this paper methods are presented for the visualisation of plant life for games and other graphics simulations in real time. Current systems generally use a very limited number of models of plants that are created in advance and loaded into the system at execution time. Real-time generation saves disk space and allows for a great variety of plants to be used in a game. The methods described here will allow the creation of interesting and varied plant life and thus produce a far richer, more appealing and engrossing environment for users