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Visual tracking is challenging due to appearance changes caused by motion, illumination, occlusion and pose, among others. For these local changes, appearance model based tracking algorithms, such as MILtracker [8], have adopted local features and most recently extended to compressive domain, namely Compressive Tracking [13], for the real-time performance. However, the motion information is missed...
A common source for controlling hand prosthesis is the myoelectric signal (MES, also termed electromyography, EMG) that are collected from human body. For a pattern recognition-based EMG control scheme, research has found that the classification accuracy obtained offline may deteriorate owing to signal instinct or changed environment, which results in a reduced system stability. Based on support vector...
The problem of multi-robot task allocation (MRTA) recently has received significant attention within the robotic research community. Despite the algorithms of the MRTA problems are growing in popularity and quality, they are scattered in different literature. In addition, the evaluation criteria among the algorithms are inconsistent. To address this issue, we overview the principal MRTA algorithms...
We propose a multi-person tracking framework using only one single camera in this paper. We utilize particle filter as the tracking framework and train a SVM classifier by reliable examples extracted from associated detections without occlusion. Based on the results of data association, we integrate the target's velocity into weights calculation to handle object occlusion assuming that fast-moving...
The Pedestrian detection using Histograms of Oriented Gradients (HOG) is the most popular method to detect a human from a picture. However, it, calculates the HOG description, will cost too much time and can't meet the real-time request for detecting pedestrian from the video surveillance system. In this paper we present a novel algorithm for detecting a human from a video. Firstly, The improved approach...
The Rapidly-exploring Random Tree (RRT) has been widely used to solve path planning problems and well suited to lots of problem domains for its probabilistically complete. However, it is not so rapid in changing environments, troubled with moving obstacles and difficult regions. In this paper, a variant of RRT is proposed which is called obstacle guided RRT (OG-RRT), aiming to plan a path in changing...
Visual tracking is challenging due to appearance changes caused by motion, illumination, occlusion and pose, among others. For these local changes, appearance model based tracking algorithms, such as MILtracker [8], have adopted local features and most recently extended to compressive domain, namely Compressive Tracking [13], for the real-time performance. However, the motion information is missed...
Extreme Learning Machine (ELM) for Single-hidden Layer Feedforward Neural Network (SLFN) has been attracting attentions because of its faster learning speed and better generalization performance than those of the traditional gradient-based learning algorithms. However, it has been proven that generalization performance of ELM classifier depends critically on the number of hidden neurons and the random...
Recent years, many vision-based vehicle detection methods have been proposed. But just a few of them paid attention to vehicle type classification in a real-time video, which is an important part in intelligent traffic system. The Haar features and Histograms of Oriented Gradients (HOG) features have been proposed as useful features for vehicle detection respectively. In this paper, we propose a method...
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