Omnidirectional cameras have been used widely to better understand surrounding environments. They are often configured as stereo to estimate depth. However, due to the optics of the fish eye lens, conventional epipolar geometry is inapplicable directly to omnidirectional camera images. Intermediate formats of omnidirectional images, such as equirect-angular images, have been used. However, stereo matching performance on these image formats has been lower than the conventional stereo due to severe image distortion near pole regions. In this paper, to address the distortion problem of omnidirectional images, we devise a novel subdivision scheme of a spherical geodesic grid. This enables more isotropic patch sampling of spherical image information in the omnidirectional camera space. By extending the existing equalarc scheme, our spherical geodesic grid is tessellated with an equalepiline subdivision scheme, making the cell sizes and in-between distances as uniform as possible, i.e., the arc length of the spherical grid cell's edges is well regularized. Also, our uniformly tessellated coordinates in a 2D image can be transformed into spherical coordinates via one-to-one mapping, allowing for analytical forward/backward transformation. Our uniform tessellation scheme achieves a higher accuracy of stereo matching than the traditional cylindrical and cubemap-based approaches, reducing the memory footage required for stereo matching by 20%.

Energy consumption is a crucial issue of mobile surveillance cameras owing to limited battery capacity. The lifetime of the system is significantly extended by the event-driven operation; the system mostly stays in sleep mode and wakes up only when an event is detected. In this paper, we propose a design of a low-energy surveillance camera that records events such as the abnormal movement of objects, or physical damage to the camera itself. Unlike conventional event-driven approaches, the proposed system records video from 10 seconds before the event detection because the most critical information is often before or at the moment of event detection, not after the detection. Two different encoders, a low-power encoder and a high-compression encoder, are employed together to implement the low-energy surveillance camera. Experimental results show that the energy consumption of the whole system is reduced by up to 74.9% (by 66.8% on average) compared with conventional always-on system.