<p>    </p> <p>Lam, Luchcha. M.S., Purdue University, May 2023. Believe in the Sound You See: The Effects of Body Type and Voice Pitch on the Perceived Audio-Visual Correspondence and Believability of Virtual Characters. Major Professor: Nicoletta Adamo. </p> <p>We examined the effects of body type and voice pitch of virtual characters’ on perceived audio-visual correspondence and believability. For our within-group study, we developed nine experimental conditions using a 3 (body type: ectomorph vs. mesomorph vs. endo- morph body types) × 3 (voice pitch: low vs. medium vs. high fundamental frequency [F0]). We found significant main effects from voice pitch and significant interaction effects between a character’s body type and voice pitch on both the level of perceived audio-visual correspondence and believability of female and male characters. For female characters, we also observed an additional significant main effect from body type and a significant interac- tion effect between the participant’s biological sex and the character’s voice pitch on both perceived audio-visual correspondence and believability. Moreover, the results show that perceived believability is highly correlated to perceived audio-visual correspondence. Our findings have important practical implications in applications where the character is meant to be an emotional or informational guide that requires some level of believability, as the findings suggest that it is possible to enhance the believability of the characters by generating appropriate voices through pitch manipulation of existing voices. </p>

Traditionally, the task of determining aircraft position and attitude for automatic control has been handled by the combination of an inertial measurement unit (IMU) with a Global Positioning System (GPS) receiver. In this configuration, accelerations and angular rates from the IMU can be integrated forward in time, and position updates from the GPS can be used to bound the errors that result from this integration. However, reliance on the reception of GPS signals places artificial constraints on aircraft such as small unmanned aerial vehicles (UAVs) that are otherwise physically capable of operation in indoor, cluttered, or adversarial environments. Therefore, this work investigates methods for incorporating a monocular vision sensor into a standard avionics suite. Vision sensors possess the potential to extract information about the surrounding environment and determine the locations of features or points of interest. Having mapped out landmarks in an unknown environment, subsequent observations by the vision sensor can in turn be used to resolve aircraft position and orientation while continuing to map out new features. An extended Kalman filter framework for performing the tasks of vision-based mapping and navigation is presented. Feature points are detected in each image using a Harris corner detector, and these feature measurements are corresponded from frame to frame using a statistical Z-test. When GPS is available, sequential observations of a single landmark point allow the point's location in inertial space to be estimated. When GPS is not available, landmarks that have been sufficiently triangulated can be used for estimating vehicle position and attitude. Simulation and real-time flight test results for vision-based mapping and navigation are presented to demonstrate feasibility in real-time applications. These methods are then integrated into a practical framework for flight in GPS-denied environments and verified through the autonomous flight of a UAV during a loss-of-GPS scenario. The methodology is also extended to the application of vehicles equipped with stereo vision systems. This framework enables aircraft capable of hovering in place to maintain a bounded pose estimate indefinitely without drift during a GPS outage.