This paper investigates how standard 3D reconstruction techniques can be adapted to work with orthographic projections of pixel art images. Reconstructing 3D models from 2D images is typically done with real world objects. However, little work has explored this problem in the con
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This paper investigates how standard 3D reconstruction techniques can be adapted to work with orthographic projections of pixel art images. Reconstructing 3D models from 2D images is typically done with real world objects. However, little work has explored this problem in the context of pixel art, which has a lower resolution, and uses stylistic colors and shading, making it a problem that requires different or adapted techniques. We implement three reconstruction algorithms based on some common practices in the field: silhouette-based intersection, spatial carving using color consistency, and gradient-based depth estimation. Results show that silhouette intersection is an effective method for simple models, but fails to capture concave regions. Spatial carving addresses this limitation, although it also fails in some use cases. An adapted depth estimation technique is also used, which most accurately captures these regions, although it does not fill in the model as well. We implement a custom Blender plugin to support user annotations and improve accuracy in some ambiguous areas. We conclude that a hybrid approach, where silhouette intersection is combined with depth estimation, gives the most accurate results, and we suggest future work that can be done on the topic, including better color merging principles, adding custom viewpoint orientations, adding support for multiple object reconstruction and using perspective projections.