Compared to open surgery, minimal invasive surgery offers reduced trauma and faster recovery. However, lack of direct
view limits space perception. Stereo-endoscopy improves depth perception, but is still restricted to the direct endoscopic
field-of-view. We describe a novel technology that reconstructs 3D-panoramas from endoscopic video streams providing
a much wider cumulative overview. The method is compatible with any endoscope. We demonstrate that it is possible to
generate photorealistic 3D-environments from mono- and stereoscopic endoscopy. The resulting 3D-reconstructions can
be directly applied in simulators and e-learning. Extended to real-time processing, the method looks promising for
telesurgery or other remote vision-guided tasks.
Once a crime has been perpetrated, forensic traces will only be persevered in the crime scene for a limited time
frame. It is therefore necessary to record a crime scene meticulously. Usually, photographs and/or videos are
taken at the scene to document it, so that later on one will know the exact place of an object. Another possibility
is to construct a three dimensional (3D) model of the crime scene. A 3D model has the advantage that you can
change the perspective and view the scene from all directions. We use a stereo camera to record the crime scene
and use these images to construct a 3D model.
A drawback of conventional (color) cameras is that they only capture features that belong to the visible part
of electromagnetic spectrum. Interesting traces with strong signatures in other parts of the spectrum could be
overlooked. For example; has a lamp or computer screen been turned on previously, is there some fluid on the
carpet? Such traces can be observed with an infrared (IR) camera that captures images in the IR part of the
spectrum.
However, it is not well understood if these traces stay visible for a sufficient amount time. Therefore, a first
set of experiments was conducted to gain some insight in the visibility degradation of different IR traces over
time. The results are discussed in this paper. Furthermore, it will be shown how adding thermal information to
the 3D model can improve crime scene understanding.
In a harbor environment threats like explosives-packed rubber boats, mine-carrying swimmers and divers must be
detected in an early stage. This paper describes the integration and use of a heterogeneous multiple camera system with
panoramic observation capabilities for detecting these small vessels in the Den Helder New Harbor in the Netherlands.
Results of a series of experiments with different targets are presented. An outlook to a future sensor package containing
panoramic vision is discussed. We also investigated several aspects of the use of electro-optical systems. As for
classification, this paper concentrates on discriminating classes of small vessels with different electro-optical systems
(visual and infrared) as part of the larger process involving an operator. It addresses both selection of features (based on
shape and texture) and ways of using these in a system to assess threats. Results are presented on data recorded in coastal
and harbor environments for several small targets.
In a harbor environment threats like explosives-packed rubber boats, mine-carrying swimmers and divers must be
detected in an early stage. This paper describes the integration and use of a heterogeneous multiple camera system with
panoramic observation capabilities for detecting these small vessels in the Den Helder New Harbor in the Netherlands.
Results of a series of experiments with different targets are presented. An outlook to a future sensor package containing
panoramic vision is discussed.
KEYWORDS: Sensors, Cameras, Land mines, Motion estimation, Stereoscopic cameras, General packet radio service, Infrared cameras, Data fusion, Metals, Infrared radiation
Vehicles that serve in the role as landmine detection robots could be an important tool for demining former conflict areas. On the LOTUS platform for humanitarian demining, different sensors are used to detect a wide range of landmine types. Reliable and accurate detection depends on correctly combining the observations from the different sensors on the moving platform. Currently a method based on odometry is used to merge the readings from the sensors. In this paper a vision based approach is presented which can estimate the relative sensor pose and position together with the vehicle motion.
To estimate the relative position and orientation of sensors, techniques from camera calibration are used. The platform motion is estimated from tracked features on the ground. A new approach is presented which can reduce the influence of tracking errors or other outliers on the accuracy of the ego-motion estimate. Overall, the new vision based approach for sensor localization leads to better estimates then the current odometry based method.
In this submission, we report on the successful field demonstration of the LOTUS landmine detection system that took place in August 2002 near the village of Vidovice, in the Northeast of Bosnia and Herzegovina.
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