• Journal of the Institute of Convergence Signal Processing
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• v.5 no.2
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• pp.96-105
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• 2004

The recovering 3D image from 2D requires the depth information for each picture element. The manual creation of those 3D models is time consuming and expensive. The goal in this paper is to estimate the relative depth information of every region from single view image with camera translation. The paper is based on the fact that the motion of every point within image which taken from camera translation depends on the depth. Motion vector using full-search motion estimation is compensated for camera rotation and zooming. We have developed a framework that estimates the average frame depth by analyzing motion vector and then calculates relative depth of region to average frame depth. Simulation results show that the depth of region belongs to a near or far object is consistent accord with relative depth that man recognizes.

• Journal of Sensor Science and Technology
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• v.7 no.6
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• pp.394-400
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• 1998

In this paper, we present a robust and fast method that enables real-time computing of axial motion component of different points of a scene from a stereo images sequence. The aim of our method is to establish axial motion maps by computing a range of disparity maps. We propose a solution in two steps. In the first step we estimate motion with a low level computing for an image point by a detection estimation-structure. In the second step, we use the neighbourhood information of the image point with morphology operation. The motion maps are established with a constant computation time without spatio-temporal matching.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.20-23
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• 1996

The block matching algorithm for the motion estimation is relatively simple to implement, and thus widely applied in image sequence coding such as H.261, MPEG- I and MPEG-2. Most techniques of the block matching method use fixed-size blocks for the motion estimation. And their success relies on the assumption that the motion within each block is uniform. But if the block size is increased to reduce the number of motion vectors for high data compression, the estimated image brings about many errors. In this paper, the variable-sized blocks are used to solve this problem. And the top down method is used to select the block size.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.6
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• pp.876-877
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• 1995

The techniques for the estimation of motion vector from the image sequence assume implicitly that the intensity of image is constant through the time. But this assumption can be distored by such causes as the added noises and the sub-pel motion following the sampling, and the errors can be generated on the motion estimation by the change of intensity. In this paper, we analyzed theoretically the effect of the change of intensity by the noise on the motion estimation with the white Gaussian noise. We know a fact that the signal may be fluctuated to reduce the effect of the noise and so the sampling rate have to make down. Also we confirmed the theoretically analysis through the experiments which investigated the relation between the noises and the sampling rates.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.63.6-63
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• 2001

For robot navigation and visual reconstruction , structure from motion (SFM) is an active issue in computer vision community and its properties are also becoming well understood. As a drawback in SFM, it is well known that the SFM methods, using small motion model such as optical flow and direct method, have inevitably motion ambiguity between translation and rotation, which is called bas-relief ambiguity. In this paper based on the robust direct method using stereo image sequence, we present a new method for improving those ambiguities. Basically, the direct method uses nearly all image pixels for estimating motion parameters and depths, and global optimization techniques are adopted for finding its solution ...

• International Journal of Contents
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• v.10 no.3
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• pp.9-16
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• 2014

Depth-image-based rendering is generally used in real-time 2D-to-3D conversion for 3DTV. However, inaccurate depth maps cause flickering issues between image frames in a video sequence, resulting in eye fatigue while viewing 3DTV. To resolve this flickering issue, we propose a new 2D-to-3D conversion scheme based on fast and robust depth-map generation from a 2D video sequence. The proposed depth-map generation algorithm divides an input video sequence into several cuts using a color histogram. The initial depth of each cut is assigned based on a hypothesized depth-gradient model. The initial depth map of the current frame is refined using color and motion information. Thereafter, the depth map of the next frame is updated using the difference image to reduce depth flickering. The experimental results confirm that the proposed scheme performs real-time 2D-to-3D conversions effectively and reduces human eye fatigue.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.171.5-171
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• 2001

Information that is acquired by adhered sensors on a body has been commonly used for the three-dimensional real-time motion capture algorithm. This paper describes realtime motion capture algorithm using computer vision. In a real-time image sequence, human body silhouette is extracted use a background subtraction between background image and the reference image. Then a human standing posture whether forward or backward is estimated by extraction of skin region in the silhoutte. After then, the principal axis is calculated in the torso and the face region is estimated on the principal axis. Feature points, which are essential condition to track the human gesture, are obtained ...

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.5
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• pp.56-65
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• 2009

Stereoscopic images consist of the left image and the right image. Thus, stereoscopic images have much amounts of data than single image. Then an efficient image compression technique is needed, the DPCM-based predicted coding compression technique is used in most video coding standards. Motion and disparity estimation are needed to realize the predicted coding compression technique. Their performing algorithm is block matching algorithm used in most video coding standards. Full search algorithm is a base algorithm of block matching algorithm which finds an optimal block to compare the base block with every other block in the search area. This algorithm presents the best efficiency for finding optimal blocks, but it has very large computational loads. In this paper, we have proposed fast disparity estimation algorithm using motion and disparity vector information of the prior frame in stereo image coding. We can realize fast disparity vector estimation in order to reduce search area by taking advantage of global disparity vector and to decrease computational loads by limiting search points using motion vectors and disparity vectors of prior frame. Experimental results show that the proposed algorithm has better performance in the simple image sequence than complex image sequence. We conclude that the fast disparity vector estimation is possible in simple image sequences by reducing computational complexities.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1224-1242
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• 2018

Aiming at motion analysis and compensation, it is essential to conduct motion detection with images. However, motion detection and tracking from low-altitude images obtained from an unmanned aerial system may pose many challenges due to degraded image quality caused by platform motion, image instability and illumination fluctuation. This research tackles these challenges by proposing a modified joint transform correlation algorithm which includes two preprocessing strategies. In spatial domain, a modified fuzzy edge detection method is proposed for preprocessing the input images. In frequency domain, to eliminate the disturbance of self-correlation items, the cross-correlation items are extracted from joint power spectrum output plane. The effectiveness and accuracy of the algorithm has been tested and evaluated by both simulation and real datasets in this research. The simulation experiments show that the proposed approach can derive satisfactory peaks of cross-correlation and achieve detection accuracy of displacement vectors with no more than 0.03pixel for image pairs with displacement smaller than 20pixels, when addition of image motion blurring in the range of 0~10pixel and 0.002variance of additive Gaussian noise. Moreover,this paper proposes quantitative analysis approach using tri-image pairs from real datasets and the experimental results show that detection accuracy can be achieved with sub-pixel level even if the sampling frequency can only attain 50 frames per second.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.2
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• pp.93-97
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• 2010

This paper presents the improved KLT(Kanade-Lucas-Tomasi) of registration of Image sequence captured by camera mounted on unmanned helicopter assuming without camera attitude information. It consists of following procedures for the proposed image registration. The initial interested points are detected by characteristic curve matching via dynamic programming which has been used for detecting and tracking corner points thorough image sequence. Outliers of tracked points are then removed by using Random Sample And Consensus(RANSAC) robust estimation and all remained corner points are classified as inliers by homography algorithm. The rectified images are then resampled by bilinear interpolation. Experiment shows that our method can make the suitable registration of image sequence with large motion.