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This paper presents a comparison of applying different clustering algorithms on a point cloud constructed from the depth maps captured by a RGBD camera such as Microsoft Kinect. The depth sensor is capable of returning images, where each pixel represents the distance to its corresponding point not the RGB data. This is considered as the real novelty of the RGBD camera in computer vision compared to...
Mobile robots are providing great assistance operating in hazardous environments such as nuclear cores, battlefields, natural disasters, and even at the nano-level of human cells. These robots are usually equipped with a wide variety of sensors in order to collect data and guide their navigation. Whether a single robot operating all sensors or a swarm of cooperating robots operating their special...
The mutual information (MI) measure has become a popular metric to assess image fusion performance. However, despite its publicity, it provides a questionable result that consistently favours additive fusion (averaging) over multi-scale decomposition (MSD) fusion algorithms. Presented is a localised variation of MI to assess image fusion performance while preserving the importance of local structural...
This paper discusses the duality between image fusion algorithms and quality metrics. It discusses odd cases where some quality metrics fail to estimate the added information and proposes a duality index that measures how suitable the metrics are to fusion algorithms. The proposed duality index serves as an objective function against which combinations of fusion algorithms, metrics, and their parameters...
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