Three-dimensional integral imaging and object detection using long-wave infrared imaging.

Abstract

We propose a passive three-dimensional (3D) imaging technique based on integral imaging using a long-wave infrared (LWIR) camera. 3D imaging can improve visualization and detection of objects in adverse environments, such as low light levels and the presence of partial occlusions, along with depth estimation by reconstructing the scene at the plane of the object. This is achieved by capturing multiple two-dimensional images, known as elemental images (EI), of a scene with each image having a unique perspective of the 3D objects. Moreover, LWIR imaging performs well in photon-limited environments due to detection of thermal radiation from an object rather than the reflected light. Once the EIs have been captured, image restoration is performed on the captured images. A 3D scene is then reconstructed and object detection using correlation filters and support vector machines is performed. Our experiments with human face detection show that 2D imaging may fail to detect occluded humans, whereas passive 3D imaging with LWIR could be successful. To the best of our knowledge, this is the first report of passive 3D integral imaging with LWIR for object detection, and in particular, in low light environments.