  In perspective cameras, images of a frontal-parallel 3D object preserve its
aspect ratio invariant to its depth. Such an invariance is useful in
photography but is unique to perspective projection. In this paper, we show
that alternative non-perspective cameras such as the crossed-slit or XSlit
cameras exhibit a different depth-dependent aspect ratio (DDAR) property that
can be used to 3D recovery. We first conduct a comprehensive analysis to
characterize DDAR, infer object depth from its AR, and model recoverable depth
range, sensitivity, and error. We show that repeated shape patterns in real
Manhattan World scenes can be used for 3D reconstruction using a single XSlit
image. We also extend our analysis to model slopes of lines. Specifically,
parallel 3D lines exhibit depth-dependent slopes (DDS) on their images which
can also be used to infer their depths. We validate our analyses using real
XSlit cameras, XSlit panoramas, and catadioptric mirrors. Experiments show that
DDAR and DDS provide important depth cues and enable effective single-image
scene reconstruction.
