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In this paper we propose a new extraction scheme for linear arranged targets in polarimetric SAR images based on a contrario theory. In this scheme, to reduce the influence of speckle, firstly a polarimetric whitening filter is applied to combine four images from different channels into a single channel image. Then a Cell-Averaging Constant False Alarm Rate detector with Weibull clutter background...
In this paper, we present a new moving object detection approach based on block texture. It can dramatically reduce the memory size when constructing the background model in a dynamic scene. The proposed background model and detection algorithm are suitable for implementing on embedded system platform which always has resource limitation. From the experimental results, our detection quality achieves...
Swimmer tracking in swimming pools is a challenging vision task due to its varying complex background. Most moving object detection methods are developed for static or partial static backgrounds, and thus can not be applied in swimmer detection problems. This work presents an approach combining mean-shift clustering and cascaded boosting learning algorithm for swimmer detection. There are three main...
This paper presents a routing approach for the mesh network on chip. This routing approach can choose the appropriate intermediate router to achieve the fast routing. It can balance the traffic load and achieve deadlock free. From the experimental results, our approach can improve at least 8.3% of the packet transmission latency comparing with the latest works. Next, the image object detection system,...
In this paper, we propose an active contour with threshold value to detect objects and at the same time get rid of unimportant parts rather than extract all information. The basic ideal of our model is to introduce a weight matrix into region-based active contours, which can enhance the weight for the main parts while filter the weak intensity, such as shadows, illumination and so on. Moreover, we...
Robust ego-motion estimation in urban environments is a key prerequisite for making a robot truly autonomous, but is not easily achievable as there are two motions involved: the motions of moving objects and the motion of the robot itself. We proposed a random sample consensus (RANSAC) based ego-motion estimator to deal with highly dynamic environments using one planar laser scanner. Instead of directly...
In this paper, we propose a method to automatically obtain a user's gesture skin color space which is used to perform gesture segmentation. The proposed approach is based on gesture skin color space that is obtained by the least squares approximations solution and Gaussian distributed model. In addition, we can also improve gesture segmentation defacement, which is caused by a complex background,...
Tracking in crowded urban areas is a daunting task. High crowdedness causes challenging data association problems. Different motion patterns from a wide variety of moving objects make motion modeling difficult. Accompanying with traditional motion modeling techniques, this paper introduces a scene interaction model and a neighboring object interaction model to respectively take long-term and short-term...
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