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Data mapping among different data standards in health institutes is often a necessity when data exchanges occur among different institutes. However, no matter rule-based approaches or traditional machine learning methods, none of these methods have achieved satisfactory results yet. In this work, we propose a deep learning method, mixture feature embedding convolutional neural network (MfeCNN), to...
Kernel principal component analysis (KPCA) is a powerful feature extraction technique. For character recognition, however, the computation cost of KPCA is too high because of much larger sample size of each class. A novel two-stage feature extraction method DL-KPCA that based on dictionary learning and KPCA is proposed for character recognition. In the first stage, with the dictionary learning method...
This paper develops an Android face recognition application for users on mobile device, and applies it in the face verification system of Samsung Galaxy SII smart phone. The developed face recognition application includes three parts, the face detection using the Viola-Jones face detection program, the feature extraction implemented by the eigenface features, and the face recognition based on the...
In this paper, we propose a new method of image classification based on SIFT-Gabor-Scale descriptors. At first, we design the patch-based SIFT-Gabor-Scale descriptor by integrating SIFT and Gabor-Scale features. Then a compact image presentation is obtained with the sparse coding spatial pyramid matching (ScSPM) method. Finally, image classification is implemented effectively with the simple linear...
This paper presents a camera calibration method for estimating the intrinsic parameters of fish-eye cameras which would be utilized in the vehicle around view monitoring system. A calibration pattern is devised to provide the information for calibrating all of the fish-eye cameras simultaneously. The diagonal projection is applied to extract the feature points on the calibration pattern. The lens...
This paper presents a real-time 3D hand posture estimation using the data from a RGB-D camera. A hierarchical method is adopted to first estimate the pose of palm and then the pose of fingers. The particle filtering algorithm with efficient particle generation for tracking the palm and fingers is proposed by analyzing the depth gradient and the contour of hand region. The finger motion model with...
Rapid increase of the amount of image data necessitates the development of efficient tools for representing visual input. In this paper, we present an approach for automatically extracting the ROI (region of interest) and that can find objects using visual attention technique. Multiple image features such as intensity, color and orientation in multiple scales are extracted to get some feature maps...
This paper presents an upper body tracking algorithm with a single monocular camera. In order to be suitable for human robot interaction, the designed method should be free to work on the moving camera platform and also can achieve real-time performance. The dimension of human posture model is extremely high, and we hereby focus on the visual extraction of head and arms. A hierarchical structure model...
This paper presents a real-time tracking system to detect and track multiple moving objects on a controlled pan-tilt camera platform. In order to describe the relationship between the targets and camera in this tracking system, the input/output hidden Markov model (HMM) is applied here in the well-defined spherical camera coordinate. Since the detection and tracking for different targets are performed...
Human face recognition plays an important role in applications such as video surveillance, human computer interface, and face image database management. This paper presents an improved face recognition method for multi-pose face recognition in color images, which addresses the problems of illumination and pose variation. At first, color multi-pose faces image features were extracted based on Gabor...
In this paper, we propose an algorithm to detect captions from news videos. The propose method only detects captions excluding other miscellaneous types of text. The algorithm makes use of the fact that the text remains in many consecutive frames to reduce the number of the processing frames. The caption beginning frame is detected first, then a caption candidate strip in the caption beginning frame...
In this paper, we propose an algorithm to detect captions from news videos. The propose method only detects captions excluding other miscellaneous types of text. The algorithm makes use of the fact that the text remains in many consecutive frames to reduce the number of the processing frames. The caption beginning frame is detected firs, then a caption candidate region in the caption beginning frame...
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