3 research outputs found
Space and camera path reconstruction for omni-directional vision
In this paper, we address the inverse problem of reconstructing a scene as
well as the camera motion from the image sequence taken by an omni-directional
camera. Our structure from motion results give sharp conditions under which the
reconstruction is unique. For example, if there are three points in general
position and three omni-directional cameras in general position, a unique
reconstruction is possible up to a similarity. We then look at the
reconstruction problem with m cameras and n points, where n and m can be large
and the over-determined system is solved by least square methods. The
reconstruction is robust and generalizes to the case of a dynamic environment
where landmarks can move during the movie capture. Possible applications of the
result are computer assisted scene reconstruction, 3D scanning, autonomous
robot navigation, medical tomography and city reconstructions
Global Shipping Container Monitoring Using Machine Learning with Multi-Sensor Hubs and Catadioptric Imaging
We describe a framework for global shipping container monitoring using machine learning with multi-sensor hubs and infrared catadioptric imaging. A wireless mesh radio satellite tag architecture provides connectivity anywhere in the world which is a significant improvement to legacy methods. We discuss the design and testing of a low-cost long-wave infrared catadioptric imaging device and multi-sensor hub combination as an intelligent edge computing system that, when equipped with physics-based machine learning algorithms, can interpret the scene inside a shipping container to make efficient use of expensive communications bandwidth. The histogram of oriented gradients and T-channel (HOG+) feature as introduced for human detection on low-resolution infrared catadioptric images is shown to be effective for various mirror shapes designed to give wide volume coverage with controlled distortion. Initial results for through-metal communication with ultrasonic guided waves show promise using the Dynamic Wavelet Fingerprint Technique (DWFT) to identify Lamb waves in a complicated ultrasonic signal