Object Detection

Stealthy object detection and recognition

Stealthy object detection and recognition


Develop a computer vision system capable of detecting hidden weapons, that are difficult to detect manually.


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 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.

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. This shows a normal image of a concealed weapon under a T-shirt, which has been processed to separate shape and texture.

Object detection

The bottom-right image shows the result of applying a novel algorithm to enhance shape – thus highlighting suspicious features.

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Theme Leader

Centre for Machine Vision

Professor Melvyn Smith
Bristol Robotics Laboratory,
University of the West of England,
Frenchay Campus, T Building,
Coldharbour Lane,
Bristol, BS16 1QY
Tel: +44 (0)117 32 86358
E-mail: Melvyn.Smith@uwe.ac.uk

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Page last updated 12 May 2016