Stealthy object detection and recognition
UWE's idea for a portable device to automatically detect and recognise potential threats to troops in war zones has succeeded under the MOD's Competition of Ideas scheme.
The successful idea has won funding to be developed into a prototype in conjunction with partners SEA (Group) Ltd. The idea put forward by UWE's team of Machine Vision experts, led by Prof Melvyn Smith, could help soldiers detect camouflaged objects or people and could enhance and recognise the shapes of 3D objects such as guns or explosives hidden under clothing.
The system, based on our expertise in photometric stereo techniques, reveals and enhances subtle shapes and surface details that may not be apparent or are deliberately concealed. Photometric stereo produces a composite image using light from at least three sources linked to a computer to derive detailed information about an object's surface.
The Technical Director of SEA's Defence Division, Peter Cooper, said "Different configurations of the portable device could be used in different task scenarios, for example a compact wearable version could be developed for work at close range, or a portable system for operation by several personnel over greater distances in the field. We look forward to working with UWE on this challenging project." The MOD received 467 entries for its Competition of Ideas, over half of which came from universities and small or medium enterprises. Sixty-six of the proposals - about one in seven - were successful and of these 22 contracts were awarded to universities. In all, these projects represent an investment of about £11 million into new ideas to enhance the UK's defence technology strategy.
As a demonstration of the technique, consider the first image above. This shows a model aeroplane placed on a planar surface with 2D images of the plane. When viewed from above (second image), it is difficult to identify the real camouflaged object from the background. Photometric stereo however, reveals the 3D structure of the scene, thus highlighting the real object.
As a second example, consider the images below. The left-hand image shows a normal photograph of several camouflaged weapons. Using our method, the shape of the items can be enhanced to clearly reveal the location and class of the concealed items (right).