A Computer Tool for 3D Shape Recovery of Fruits

Characterizing a fruit’s mechanical behavior is an important step towards reducing economic losses due to bruising. Several 3D scanning technologies allow to obtain the external geometry of a fruit, but no easily accessible tools exist for the acquisition of the geometry of internal structures such as the core. We propose a low-cost destructive method for tomographic reconstruction of a fruit from scanned slices. A method for overcoming the difficulties in registering the different images is also presented.

Perception of 3D Symmetrical and Nearly Symmetrical Shapes

The human visual system uses priors to convert an ill-posed inverse problem of 3D shape recovery into a well-posed one. In previous studies, we have demonstrated the use of priors like symmetry, compactness and minimal surface in the perception of 3D symmetric shapes. We also showed that binocular perception of symmetric shapes can be well modeled by the above-mentioned priors and binocular depth order information. In this study, which used a shape-matching task, we show that these priors can also be used to model perception of near-symmetrical shapes. Our near-symmetrical shapes are asymmetrical shapes obtained from affine distortions of symmetrical shapes. We found that the perception of symmetrical shapes is closer to veridical than the perception of asymmetrical shapes is. We introduce a metric to measure asymmetry of abstract polyhedral shapes, and a similar metric to measure shape dissimilarity between two polyhedral shapes. We report some key observations obtained by analyzing the data from the experiment. A website was developed with all the shapes used in the experiment, along with the shapes recovered by the subject and the shapes recovered by the model. This website provides a qualitative analysis of the effectiveness of the model and also helps demonstrate the goodness of the shape metric.