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State-of-the-art single image dehazing algorithms have some challenges to deal with images captured under complex weather conditions because their assumptions usually do not hold in those situations. In this paper, we develop a deep transmission network for robust single image dehazing. This deep transmission network simultaneously copes with three color channels and local patch information to automatically...
Background subtraction is a traditional method for detecting objects in stationary background. However, this traditional method is difficult to detect objects accurately in the real world, because the background is usually cluttered and not completely static. In this paper, we propose an object detection approach using Ant Colony System (ACS) in a MAP-MRF framework. For object segmentation, a MAP-MRF...
This paper presents a novel method for real-time obstacle detection and recognition in natural terrain for a field mobile robot using a image information, geometric information and support vector machine(SVM). Firstly, the scene is divided into two distinct regions: interest regions and uninterested regions. Then detected obstacle points are clustered into objects on the basis of their geometric information,...
In order to correctly sense incline terrain, its geometrical calculated model is analyzed. Based on the change trend of distance between the mobile robot and slope, their relative position can be determined. Then a novel method which takes the use of the powerful nonlinearity approach capability of RBF network is introduced to estimate the slope of the terrain with respect to the robot's current angular...
Object detection is an important basis for tracking and recognition in visual surveillance systems via stationary cameras. The traditional background subtraction method is difficult to detect objects accurately in the scenes, because the background is usually cluttered and not completely static. In this paper, we propose a new method for background subtraction based on adaptive non-parametric kernel...
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