A robust visual servoing system is investigated on a humanoid robot which grasps a brush in Chinese calligraphy task.The system is implemented based on uncalibrated visual servoing controller utilizing Kalman-Bucy fil...A robust visual servoing system is investigated on a humanoid robot which grasps a brush in Chinese calligraphy task.The system is implemented based on uncalibrated visual servoing controller utilizing Kalman-Bucy filter,with the help of an object detector by continuously adaptive MeanShift(CAMShift) algorithm.Under this control scheme,a humanoid robot can satisfactorily grasp a brush without system modeling.The proposed method is shown to be robust and effective through a Chinese calligraphy task on a NAO robot.展开更多
Accurately finding the region of interest is a very vital step for segmenting organs in medical image processing.We propose a novel approach of automatically identifying region of interest in Computed Tomography Image...Accurately finding the region of interest is a very vital step for segmenting organs in medical image processing.We propose a novel approach of automatically identifying region of interest in Computed Tomography Image(CT)images based on temporal and spatial data.Our method is a 3 stages approach,1)We extract organ features from the CT images by adopting the Hounsfield filter.2)We use these filtered features and introduce our novel approach of selecting observable feature candidates by calculating contours’area and automatically detect a seed point.3)We use a novel approach to track the growing region changes across the CT image sequence in detecting region of interest,given a seed point as our input.We used quantitative and qualitative analysis to measure the accuracy against the given ground truth and our results presented a better performance than other generic approaches for automatic region of interest detection of organs in abdominal CT images.With the results presented in this research work,our proposed novel sequence approach method has been proven to be superior in terms of accuracy,automation and robustness.展开更多
基金Supported by the National Natural Science Foundation of China(No.61221003)
文摘A robust visual servoing system is investigated on a humanoid robot which grasps a brush in Chinese calligraphy task.The system is implemented based on uncalibrated visual servoing controller utilizing Kalman-Bucy filter,with the help of an object detector by continuously adaptive MeanShift(CAMShift) algorithm.Under this control scheme,a humanoid robot can satisfactorily grasp a brush without system modeling.The proposed method is shown to be robust and effective through a Chinese calligraphy task on a NAO robot.
基金This work was supported by the National Natural Science Foundation of China(Nos.61772242,61572239,61402204)Research Fund for Advanced Talents of Jiangsu University(14JDG141)+2 种基金Qing Lan ProjectChina Postdoctoral Science Foundation(No.2017M611737)Zhenjiang social development project(SH2016029).
文摘Accurately finding the region of interest is a very vital step for segmenting organs in medical image processing.We propose a novel approach of automatically identifying region of interest in Computed Tomography Image(CT)images based on temporal and spatial data.Our method is a 3 stages approach,1)We extract organ features from the CT images by adopting the Hounsfield filter.2)We use these filtered features and introduce our novel approach of selecting observable feature candidates by calculating contours’area and automatically detect a seed point.3)We use a novel approach to track the growing region changes across the CT image sequence in detecting region of interest,given a seed point as our input.We used quantitative and qualitative analysis to measure the accuracy against the given ground truth and our results presented a better performance than other generic approaches for automatic region of interest detection of organs in abdominal CT images.With the results presented in this research work,our proposed novel sequence approach method has been proven to be superior in terms of accuracy,automation and robustness.
