In 2024, the VR180 3D short film “Love Letter to Skating” was produced as part of a Curtin University HIVE Summer Internship project conducted by Curtin University student Cassandra Edwards (Cass for short). The film topically explores Cass’s fascination with skating since her childhood years. The location for the shoot was Hyde Park, a beautiful inner-city park with extensive gardens and large over-hanging trees in Perth, Western Australia. The production was filmed using a Canon R5C camera fitted with a Canon Dual Fisheye lens. This particular paper focuses on the stereoscopic post-production workflow. All stereoscopic content filmed natively with two lens cameras have some level of stereoscopic alignment errors. In the post-production stage, the native dual-fisheye 8K footage from the camera was converted to equirectangular format using the Canon EOS VR Utility software. The equirectangular VR180 3D footage was rectified using Stereoscopic Movie Maker V2 software. The rectified footage was then imported into Adobe Premiere where it was edited and combined with sound, music and graphics for the final production. Computer graphics were composited into the final film at the correct depth within Premiere. The final production premiered at the MINA 2024 – the 13th International Mobile Innovation Screening and Smartphone Film Festival 8th November 2024.
Pigment classification of paintings is considered an important task in the field of cultural heritage. It helps to analyze the object and to know its historical value. This information is also essential for curators and conservators. Hyperspectral imaging technology has been used for pigment characterization for many years and has potential in its scientific analysis. Despite its advantages, there are several challenges linked with hyperspectral image acquisition. The quality of such acquired hyperspectral data can be influenced by different parameters such as focus, signal-to-noise ratio, illumination geometry, etc. Among several, we investigated the effect of four key parameters, namely focus distance, signal-to-noise ratio, integration time, and illumination geometry on pigment classification accuracy for a mockup using hyperspectral imaging in visible and near-infrared regions. The results obtained exemplify that the classification accuracy is influenced by the variation in these parameters. Focus distance and illumination angle have a significant effect on the classification accuracy compared to signal-to-noise ratio and integration time.