Recent advancements in laser and visible light sensor technology allows for the collection of photorealistic 3D scans of large scale spaces. This enables the technology to be used in real world applications such as crime scene investigation. The 3D models of the environment obtained with a 3D scanner capture visible surfaces but do not provide semantic information about salient features within the captured scene. Later processing must convert these raw scans into salient scene structure. This paper describes ongoing research into the generation of semantic data from the 3D scan of a crime scene to aid forensic specialists in crime scene investigation and analysis. MotivationThe goal of the CBRN Crime Scene Modeler project is the development and field evaluation of technologies for Canadian Conference on Computer and Robot Vision 978-0-7695-3153-3/08 $25.00
For systems to become truly autonomous it is necessary that they be able to interact with complex real-world environments. In this article we investigate techniques and technologies to address the problem of the acquisition and representation of complex environments such as those found underwater. The underwater environment presents many challenges for robotic sensing including highly variable lighting and the presence of dynamic objects such as fish and suspended particulate matter. The dynamic six-degree-of-freedom nature of the environment presents further challenges due to unpredictable external forces such as current and surge. In order to address the complexities of the underwater environment we have developed a stereo vision-inertial sensing device that has been successfully deployed to reconstruct complex 3-D structures in both the aquatic and terrestrial domains. The sensor combines 3-D information, obtained using stereo vision, with 3DOF inertial data to construct 3-D models of the environment. Semiautomatic tools have been developed to aid in the conversion of these representations into semantically relevant primitives suitable for later processing. Reconstruction and segmentation of underwater structures obtained with the sensor are presented.
The underwater environment presents many challenges for robotic sensing including highly variable lighting and the presence of dynamic objects such as fish and suspended particulate matter. The dynamic six-degree-of-freedom nature of the environment presents further chalenges due to unpredictable external forces such as current and surge. Despite these chalenges the aquatic environment presents many real and practical applications for robotic systems. A common requirement of many of these tasks is the need to construct accurate 3D representations of specific environmental structures. In order to address these needs we have developed a stereo visioninertial sensing device that has been successfuly deployed to reconstruct complex 3D structures in both the aquatic and terrestrial domains. The sensor combines 3D information, obtained using stereo vision algorithms, with 3DOF inertial data to construct 3D models of the environment. The resulting model representation is then converted to a textured polygonal mesh for later processing. Semi-automatic tools have been developed to aid in the processing of these representations. Reconstruction and segmentation of coral and other underwater structures Fig. 1. The AQUA robot shown with a diver for scale. The robot is powered obtained with the sensor are presented. by six fins which give it direct access to five degrees of freedom of motion.The robot can operate completely autonomously although it is shown here
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