Virtual Access to STEM Careers: In the Field Experiments.

The Virtual Access to STEM Careers (VASC) project is an intertwined classroom and virtual reality (VR) curricular program for third through fourth graders. Elementary school students learn about and take on the roles and responsibilities of STEM occupations through authentic, problem-based tasks with physical kits and immersive VR environments. This article reports on a round of curriculum and virtual environment development and in-classroom experimentation that was guided by preliminary results gathered from our initial VASC prototyping and testing. This specific iteration focuses on curriculum for learning about sea turtles and tasks regularly completed by park rangers and marine biologists who work with these creatures and a new backend data collection component to analyze participant behavior. Our results showed that educators were able to setup and integrate VASC into their classrooms with relative ease. Elementary school students were able to learn how to interface with our system quickly and enjoyed being in the environment, making a positive link to STEM education.

Enhancing Film Education Learning Outcomes With Virtual Experiences.

This article details a system titled "Camera as Mediator" that was built to aid undergraduate Film Studies students study camera placement and shot composition techniques. Learning how camera placement impacts a film is a common educational outcome in undergraduate Film Studies classes. However, building a controlled set with proper lighting, actors, and props is a cost- and time-prohibitive task in a typical introductory course. A virtual system can give students more hands-on experience and leave ample time to focus on core learning outcomes. To this end, we constructed a photorealistic virtual environment to replicate a scene from the Charlie Chaplin film "The Gold Rush" using computer-generated models and three-dimensional scans of actors dressed as the characters from the movie. An interface was designed to allow students to navigate around the scene with a virtual camera and capture shots from perspectives not visible in the original movie. By saving and comparing these different shots, students are easily able to explore how the mood and feel of a story changes with the camera's perspective. Doing this virtually enables undergraduate students in large classes and/or online classes and with potentially limited time and equipment to study film making techniques in greater depth than they would otherwise.

An Ensemble Approach to Image Matching Using Contextual Features.

We propose a contextual framework for 2D image matching and registration using an ensemble feature. Our system is beneficial for registering image pairs that have captured the same scene but have large visual discrepancies between them. It is common to encounter challenging visual variations in image sets with artistic rendering differences or in those collected over a period of time during which the lighting conditions and scene content may have changed. Differences between images may also be caused using a variety of cameras with different sensors, focal lengths, and exposure values. Local feature matching techniques cannot always handle these difficulties, so we have developed an approach that builds on traditional methods to consider linear and histogram of gradient information over a larger, more stable region. We also present a technique for using linear features to estimate corner keypoints, or pseudo corners, that can be used for matching. Our pipeline follows this unique matching stage with homography refinement methods using edge and gradient information. Our goal is to increase the size of accurate keypoint match sets and align photographs containing a combination of man-made and natural imagery. We show that incorporating contextual information can provide complimentary information for scale invariant feature transform and boost local keypoint matching performance, as well as be used to describe corner feature points.