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The catadioptric vision system has seen an increasing interest due to its larger field of view. In this work, we present a method for calibrating the parabolic camera which consists of a parabolic mirror and an orthographic camera. Here, the mirror parameter and its positions are estimated from a closed-form solution with the assumption of the known intrinsic parameters of the camera a priori. The...
Intelligent rehabilitation system has become a hot topic. In home rehabilitation system, the real-time tracking of human motion is very important. In this paper, it presents a modified CamShift (continuously adaptive mean shift) algorithm, which can track human limb motion in real time. Considering the limb motion and selected color probability distribution all together, we put forwards the modified...
In this paper, we present a SIFT based Slope K method which is faster and more robust than the classical SIFT in landmark based localization. First, the slope k value can be used to erase mismatched feature points (outliers) of the two compared images. Second, the y position is determined by the slope k value. Therefore, the Slope K method is able to localizes about twice as more accurate as the classical...
3D model matching has been widely studied in computer vision, graphics and robotics. While there is much success made in the matching of natural objects, most of these approaches consider smooth surfaces and are not suitable for computer aided design (CAD) models because of their complex topology and singular structures. This paper presents a novel spectral approach for the 3D CAD model matching in...
The advantage of the optical-flow-based visual servo methods is that features of the moving object do not need to be known in advance. Therefore, they can fit for demands of versatile positioning and tracking tasks in the real world. Nevertheless, it is difficult to achieve satisfactory tracking performance for fast moving objects using these standard approaches. The purpose of this paper is to implement...
In this paper we propose a new method of detecting moving objects from a moving camera based on SIFT(The Scale Invariant Feature Transform) features matching and dynamic background modeling. Firstly, feature points are extracted by SIFT algorithm to compute the affine transformation parameters of camera motion, and guided by RANSAC to remove the outliers. We adopt background subtraction approach to...
Automatic reconstruction of unknown 3-D objects is a main part of the machine vision technology and it has a variety of applications such as robot navigation, medical imaging and industrial inspection, etc. In this paper, a new view planning method for reconstructing unknown 3-D models automatically was proposed based on the limit visual surface. Firstly, the visual region of the laser-vision system...
Efficiently and accurately detecting pedestrian plays a very important role in many computer vision applications such as Intelligent Transportation System and Safety Driving Assistant. This paper puts forwards a two-stage pedestrian detection method based on machine vision. Firstly, the expanded Haar-like characteristic is selected and calculated using integral map and the pedestrian detection cascaded...
Detection of local feature covariant region is a new technology of image contents and image semantic representations, and it has become an important foundation of the image recognition, learning and understanding. First, a Laplace of Gaussian corner detection method is proposed based on edge contour curves, in the meantime, a new local feature descriptor, named covariant support region, is introduced...
Keypoints are important features in the perceptual system of humans. They provide important information for focus-of-attention (FoA) and object categorization/recognition. Different types of keypoints have been used in computer vision applications. In this paper, we propose a method which extracts ??salient?? points in the meaning of biological vision by utilizing the multi-scale Gabor energy operator...
In order to solve the problem of betel nuts' misclassification by manual ways, an automatic classification method based on computer vision is proposed in this paper. The new method achieves automatic classification by extracting color features, shape features and texture features of betel nuts. Experiments show that this method has good effect, high speed and can satisfy the real-time classification...
Local descriptors computed for key-points or interest regions are successfully applied in computer vision area. Among various descriptors, the SIFT based descriptors have been demonstrated to perform best. However, their computational cost is very expensive. In the paper, we propose a fast local descriptor, which is composed of the coding computed from the image patch centered at each key-point. The...
This paper presents a vision based human machine interface (HMI) for the Xbox. It applies feature tracking algorithms to recognize user's head gestures and translates them into commands for the game. The pyramidal implementation of Lucas Kanade feature tracking is used to trace the optical flows in a sequence of frames. The experimental results show the feasibility of the proposed vision based interface,...
The accuracy of corner detection is critical for many machine vision applications. A novel corner detector based on video is proposed in this paper. The corner detector can effectively constrain camera noise by using multiple frames from video. The kernel of this method is the similarity algorithm which including a special representation of binary image, a robust template, a simple similarity function...
Image segmentation is an important and difficult task in computer vision applications. Various methods have been introduced in the past to use gray-level histogram in deciding the segmentation threshold for monochrome images. With the reducing price of color cameras, different color spaces have also been considered in color image based segmentations. In this paper, a study of the effect of color spaces...
Solving the fundamental matrix is an important research topic in computer vision. The relationship between the epipole and the parameters of fundamental matrix can be found from the fundamental matrix of rank 2. A new model is equivalent to the fundamental matrix of rank 2. The model of the fundamental matrix, whose rank equals 2 can be provided. According to the relationship between the parameters,...
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