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Traditional interfaces for interacting with 3D models in virtual environments lack support for spatiotemporal 3D models such as point clouds and meshes generated by markerless capture systems. We present a virtual reality (VR) interface that enables the user to perform spatial and temporal interactions with spatiotemporal 3D models. To accommodate the high volume of spatiotemporal data, we provide a data format for spatiotemporal 3D models which has an average speedup of 3.84 and a space reduction of 43.9% over traditional model file formats. We enable the user to manipulate spatiotemporal 3D data using gestures intuitive from real-world experience or by using a VR user interface similar to traditional 2D visual interactions. 

We present a microenvironment of multiple cameras to capture multi-viewpoint time-lapse videos of objects showing spatiotemporal phenomena such as aging. Our microenvironment consists of four synchronized Raspberry Pi v2 cameras triggered by four corresponding Raspberry Pi v3 computers that are controlled by a central computer. We provide a graphical user interface for users to trigger captures and visualize multiple viewpoint videos. We show multiple viewpoint captures for objects such as fruit that depict shape changes due to water volume loss and appearance changes due to enzymatic browning. 

We provide an approach to reconstruct spatiotemporal 3D models of aging objects such as fruit containing time-varying shape and appearance using multi-view time-lapse videos captured by a microenvironment of Raspberry Pi cameras. Our approach represents the 3D structure of the object prior to aging using a static 3D mesh reconstructed from multiple photographs of the object captured using a rotating camera track. We manually align the 3D mesh to the images at the first time instant. Our approach automatically deforms the aligned 3D mesh to match the object across the multi-viewpoint time-lapse videos. We texture map the deformed 3D meshes with intensities from the frames at each time instant to create the spatiotemporal 3D model of the object. Our results reveal the time dependence of volume loss due to transpiration and color transformation due to enzymatic browning on banana peels and in exposed parts of bitten fruit.