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Reliable surface normal computation is fundamental for a broad range of computer vision application areas, e.g. object segmentation, classification and recognition. Naturally, the surface normal is computed on the acquired depth data, whereby the normal quality is dependent on noise performance and resolution of the underlying image modality. The tendency of combining different imaging sensors into...
We propose a new method for fitting an ellipse to a point sequence extracted from an image. This method can fit an ellipse if a point sequence consists of elliptic arcs and non-elliptic arcs such as line segments. Assuming that input points are spatially connected, we iteratively select inlier points and fit an ellipse to them by computing curvatures of the residual graph. By using simulated data...
This paper presents a novel outlier removal method which is capable of fitting ellipse in real-time under high outlier rate, based on the phenomenon that outliers generated by ellipse edge point detector are likely to appear as groups due to real-world nuisances, such as under partial occlusion or illumination change. To confront the grouped outliers while maintaining the fitting efficiency, we introduce...
Sparse bundle adjustment (SBA) is the state of the art method for simultaneously optimizing a set of camera poses and 3D points. The multibody bundle adjustment optimizes the static scene and the moving rigid object(s). The result is one camera path representing the main camera motion and virtual camera path(s) for each of the independently moving objects in the scene. The bundle adjustment for the...
Calibrating the response function of a line scanner is very important in many fields of computer vision. We propose a method to reduce nonequivalence present in response functions of pixels. Contrary to current state-of-the-art methods our method uses a linear light source which is usually attached to line scanners for pixel-wise calibration. We define a radiant intensity function for a linear light...
Noise is an impairment which often occurs in both film and digital video and severely degrades the viewing experience of the content. In this work, we propose a two-phase algorithm for film an video denoising. In the first phase, the concept of semi-local shrinkage functions is used to effectively separate noise from image structure. In the second phase, we show how to fuse the result images of the...
This paper provides a geometrical aspect of Fisher's linear discriminant analysis (FLDA), which has been widely used owing to its simple formulation and low computational costs. Our approach is based on a new framework of pattern recognition that can be modelded by a communication of class information. This model is quite different from a commonly used framework of pattern recognition as a mapping...
Recent years have shown increases in virtual 3D perception and applications, many of these applications require 3D model reconstruction from high quality LIDAR scans. High quality 3D models may be acquired from a collection of overlapping LIDAR scans which need to be registered or aligned to a common coordinate system. This paper investigates the use of a novel implementation of trilateration for...
Distributed processing is a new paradigm to analyse the huge volume of video data in camera networks. This paper addresses the problem of distributed single target tracking considering false positives and missed detections. Target tracking is modelled as a dynamic state estimation problem with nonlinear process and measurement model. We propose to use the sigma point information filters combined with...
This paper presents a spatial domain image watermarking method based on regularized filter. In the proposed method, a watermark image is embedded into a host color image directly by modifying the blue color component. The watermarkmark strength is controlled by two factors, i.e. a constant value and the luminance within a local embedding area. The prediction of the original host image is obtained...
Registration is a fundamental problem in a myriad of applications ranging from heritage reconstruction to industrial applications. Descriptors are an important part of the registration pipeline as well as a very active research field. However, the sets used to illustrate descriptor performance have often undergone several preprocessing steps such as noise filtering, hole filling or outlier removal...
In this paper, we propose a prediction model for breathing pattern based on observations from CBCT raw projection images. From the raw CBCT projections the diaphragm apex position is measured, which in turn is used for the state estimation. We use a novel state space model followed by an Unscented Kalman Filter (UKF). Our method is compared with one of the successful models called Local Circular Motion...
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