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In this paper, we perform 3-Dimensional (3D) clustering based on the Outdoor-to-Indoor (O2I) wideband 3D multiple-input-multiple-output (MIMO) channel measurement at 3.5 GHz. Clusters are identified by KPowerMeans algorithm. Based on analysis on clustering results, we modified the definition of Multiple component distance (MCD) to split the bounding of azimuth and elevation, which can obtain larger...
Assessing and selecting relevant visual cues is crucial for rapid saliency estimation and visual search. Here, we derive a new optimal feature modulation strategy to maximize the relative salience of the target, in which the top-down weight on a feature map depends on its stimulation intensity ratio (SIR) between the target and the distractors. The stimulation intensity is determined by two factors,...
Finding optimal top-down feature gains plays a key role in modeling task-driven visual attention mechanisms. Some studies suggest that the ratio of the mean salience of the target to the distractors can be used to determine the weights for the feature maps during the searching process, but this works well only if the salience distribution in the feature map is uniform, which is seldom seen in natural...
A novel mobile robot based gas source localization method in which the top-down visual attention mechanism (TDVAM) is combined with shape analysis is proposed. At each location, three different images which cover the scene in front of the robot are captured via changing the horizontal angle of an onboard pan/tilt camera. In each image, three salient regions are computed using TDVAM model, and maximal...
The integration of bottom-up, image-driven cues and perceptual properties of the human visual system (HVS) is crucial for the selection of salient locations. The previous studies have mainly focused on the bottom-up cues. In this paper, we propose a new model that takes both two factors into consideration. More specifically, two bottom-up conspicuity maps for early-visual features (i.e., intensity...
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