KEYWORDS: Sensors, 3D acquisition, 3D modeling, Detection and tracking algorithms, 3D image processing, Image sensors, Data modeling, Computer simulations, Laser imaging, Stereoscopy
This paper reports the successful application of automatic target recognition and identification (ATR/I) algorithms to
simulated 3D imagery of 'difficult' military targets. QinetiQ and Selex S&AS are engaged in a joint programme to build
a new 3D laser imaging sensor for UK MOD. The sensor is a 3D flash system giving an image containing range and
intensity information suitable for targeting operations from fast jet platforms, and is currently being integrated with an
ATR/I suite for demonstration and testing.
The sensor has been extensively modelled and a set of high fidelity simulated imagery has been generated using the
CAMEO-SIM scene generation software tool. These include a variety of different scenarios (varying range, platform
altitude, target orientation and environments), and some 'difficult' targets such as concealed military vehicles. The
ATR/I algorithms have been tested on this image set and their performance compared to 2D passive imagery from the
airborne trials using a Wescam MX-15 infrared sensor and real-time ATR/I suite.
This paper outlines the principles behind the sensor model and the methodology of 3D scene simulation. An overview of
the 3D ATR/I programme and algorithms is presented, and the relative performance of the ATR/I against the simulated
image set is reported. Comparisons are made to the performance of typical 2D sensors, confirming the benefits of 3D
imaging for targeting applications.
Primarily focused at military and security environments where there is a need to identify humans covertly and remotely; this paper outlines how recovering human gait biometrics from a multi-spectral imaging system can overcome the failings of traditional biometrics to fulfil those needs. With the intention of aiding single camera human gait recognition, an algorithm was developed to accurately segment a walking human from multi-spectral imagery. 16-band imagery from the image replicating imaging spectrometer (IRIS) camera system is used to overcome some of the common problems associated with standard change detection techniques. Fusing the concepts of scene segmentation by spectral characterisation and background subtraction by image differencing gives a uniquely robust approach. This paper presents the results of real trials with human subjects and a prototype IRIS camera system, and compares performance to typical broadband camera systems.
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