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Recent methods for object co-segmentation focus on discovering single co-occurring relation of candidate regions representing the foreground of multiple images. However, region extraction based only on low and middle level information often occupies a large area of background without the help of semantic context. In addition, seeking single matching solution very likely leads to discover local parts...
In this paper two methods for blind source separation of nonstationary signals, such as electroencephalogram output, applied to time frequency distributions are compared through implementation in a virtual instrument. Both methods are based on image processing approaches, but adopt different strategies for solving the blind source separation problem: the first method is based on a data clustering...
Motion detection, objects extraction and motion estimation are critical problems in automatic video surveillance and scene understood applications. In this paper, we propose a novel motion detection and object extraction method based on Histogram of disparity between neighborhood frames. Disparity is generated from the pixel changing during the target moves in video frame. Adjustable block matching...
This paper presents a text detection method that combines with an image rectification. Since texts in natural scenes are not always observed in frontal view, image rectification is needed to robustly recognize them in OCR. A reference pixel that is part of the desirable text area is given by user since this is the easiest way to give the priors. In text detection, first, foreground pixels are extracted...
Considering the increasing need of the contents of 3D video, it is significant to do some research in 2D-to-3D conversion. The depth map is necessary for this processing. In this paper, we propose an effective method to estimate the depth information of the low depth field images of static scenes. Firstly, construct a high-order statistics (HOS) map, which represents the high-frequency components...
In this paper, we present an algorithm that is to estimate the position of a hand-held camera with respect to terrestrial LiDAR data. Our input is a set of 3D range scans with intensities and one or a set of 2D uncalibrated camera images of the scene. The algorithm that automatically registers range scans and 2D images is composed of following steps. In the first step, we project the terrestrial LiDAR...
We present a novel segment extraction and segment-based depth estimation technique. Proposed segment extraction technique exploits depth and motion information of segments between frames as well as color information. We firstly divide each frame of reference view into foreground and background areas based on initial depth information obtained from time-of-flight (TOF) camera. Then we extract segments...
This paper proposes an approach for 2D-to-3D conversion for multiview displays. It employs an object-based approach where objects at large depth differences are first segmented by semi-automatic tools. Appropriate depth values are assigned to these objects and the missing image pixels at the background are filled in by inpainting techniques so that different views of the image can be synthesized....
An algorithm of adaptive deformation estimation of moving object in mean-shift tracking method is developed. Firstly, the differences between object and background in the weight image associated with the target candidate region are analyzed. By their different distributions, the area estimation of the target is converted into the task of image segmentation. The threshold is automatically selected...
Mean shift spectral clustering (MSSC) brings us an alternative for image segmentation. However, owing to being based on the classical Parzen window estimator (PW) and employing the full data sample for density estimation, the usefulness of MSSC is weakened. In this paper, the improved mean shift spectral clustering (IMSSC) algorithm is proposed by replacing PW with the reduced set density estimator...
This paper proposes an efficient and flexible interactive object segmentation approach using kernel density estimation based graph cuts. First, the user draws scribbles to roughly mark the interested object and background, respectively, and the likelihood of object versus background is evaluated for each pixel using nonparametric kernel density estimation. Then pixels are globally classified into...
This paper describes a particle filter based approach for estimating the ground plane from an image sequence. Based on a Bayesian framework, the particle filter provides a robust estimation of the plane parameters, since it can handle non-linearities, while allowing a high flexibility for integrating new cues into the system. Furthermore, the different modes of the resulting probability density function...
Aiming at the computational burden of template-based SAR target classification, an approach of SAR target classification utilizing aspect information is presented. First, estimate target aspect from peaks. Then consider the aspect as cueing information to reduce the search space. Finally the candidate target is declared by matching against those templates under aspect constraint. The proposed method...
In a conventional traffic lights controller, the lights either change at constant cycle times or at times proportional to the length of each leg of the intersection. Such approaches clearly are not perfect for optimizing traffic flow. Waiting times proportional to lane length may work well for a single-lane road but when roads with multiple lanes are considered the solution would not be optimal. The...
The paper presents two different methods to deal with the problem of iris segmentation: an agent-based method capable to localize the center of the pupil and a method to process the iris boundaries by a multiple views approach. In the first method, an agent corresponds to the coordinates of a specific point of analysis in the input image. A population of agents is deployed in the input image, then,...
Methods based on deformable model have been widely used in deformable image segmentation. The segmentation quality of this kind of methods strongly relies on its initialization. If the initiation isn't accurate, the segmentation result will not be satisfactory. To solve this problem, we propose a new deformable image cascade segmentation method. In the method, the MSRF and SMAP will be used to estimate...
This paper addresses an efficient vision based motion estimation method of robot systems for the ego-motion compensation using type-2 fuzzy sets. Every intelligent robot system like walking robots, service robots, automatic vehicles should have the ability to autonomously recognize its surroundings and to make right decisions under unknown environment. To enable a robot system to do this, ego-motion...
This paper addresses an efficient the vision based motion estimation method of a humanoid robot for the ego-motion compensation using type-2 fuzzy sets. A humanoid robot should have the ability to autonomously recognize its surroundings and to make right decisions under unknown environment. To enable a humanoid robot to do this, ego-motion compensation for a humanoid robot is mandatory. Therefore,...
The intensity value of each voxel in a brain MR image is considered to be a linear combination of signal intensities emitted from protons in aqueous and lipid environments inside that voxel. A novel model describing the proton density (PD) and fraction of protons in aqueous environment (Water Fraction - WF) as independent sources of an MR image is suggested. We consider an input set of registered...
The amplitude of the BOLD signal depends heavily upon the resting blood volume fraction (V0). However, most existing haemodynamic data assimilation studies pretermit such concern through assigning arbitrarily the value in a physiological plausible range. In this work, we presented the first exploration of the influence of the fraction V0 to model estimation, where the exact value of V0 was calibrated...
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