• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.408-412
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• 2009

In this paper, a new efficient algorithm for global motion estimation is proposed. This algorithm uses a previous 4-parameter model based global motion estimation algorithm and M-estimator for improving the accuracy and robustness of the estimate. The first algorithm uses the block based motion vector fields and which generates a coarse global motion parameters. And second algorithm is M-estimator technique for getting precise global motion parameters. This technique does not increase the computational complexity significantly, while providing good results in terms of estimation accuracy. In this work, an initial estimation for the global motion parameters is obtained using simple 4-parameter global motion estimation approach. The parameters are then refined using M-estimator technique. This combined algorithm shows significant reduction in mean compensation error and shows performance improvement over simple 4-parameter global motion estimation approach.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.216-218
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• 2009

This paper proposes an image processing algorithm to stabilize shaken scenes of UAV(Unmanned Aerial Vehicle) caused by vehicle self-vibration and aerodynamic disturbance. The proposed method stabilizes images by compensating estimated shake motion which is evaluated from global motion. The global motion between two continuous images modeled by 6 parameter warping model is estimated by non-linear square method based on Gauss-Newton algorithm with excluding outlier region. The shake motion is evaluated by subtracting the global motion from aerial vehicle motion obtained by averaging global motion. Experimental results show that the proposed method stabilize shaken scenes effectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.8
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• pp.1423-1443
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• 2011

Background compensation plays an important role in detecting and isolating object motion in visual tracking. Here, we propose a Genetic Hough Transform, which combines the Hough Transform and Genetic Algorithm, as a method for eliminating background motion. Our method can handle cases in which the background may contain only a few, if any, feature points. These points can be used to estimate the motion between two successive frames. In addition to dealing with featureless backgrounds, our method can successfully handle motion blur. Experimental comparisons of the results obtained using the proposed method with other methods show that the proposed approach yields a satisfactory estimate of background motion.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1991.10a
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• pp.81-85
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• 1991

In this paper, we present a motion compensated video compression method based on both block and object motions. A simplified objectoriented motion parameter is estimated from the block based motion vectors. A decision rule for the global or local MCP modes is established. Simulation results show that the proposed method has lower bit-rates than the BMA based method at the same reconstruction errors.

• The KIPS Transactions:PartB
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• v.9B no.5
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• pp.563-570
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• 2002

Robust extraction of 3D facial features and global motion information from 2D image sequence for the MPEG-4 SNHC face model encoding is described. The facial regions are detected from image sequence using multi-modal fusion technique that combines range, color and motion information. 23 facial features among the MPEG-4 FDP (Face Definition Parameters) are extracted automatically inside the facial region using color transform (GSCD, BWCD) and morphological processing. The extracted facial features are used to recover the 3D shape and global motion of the object using paraperspective camera model and SVD (Singular Value Decomposition) factorization method. A 3D synthetic object is designed and tested to show the performance of proposed algorithm. The recovered 3D motion information is transformed into global motion parameters of FAP (Face Animation Parameters) of the MPEG-4 to synchronize a generic face model with a real face.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.2
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• pp.35-44
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• 2002

The translation and the rotation of camera occur global motion which affects all over the frame in video sequence. With the video sequences containing global motion, it is practically impossible to extract exact video objects and to calculate genuine object motions. Therefore, high compression ratio cannot be achieved due to the large motion vectors. This problem can be solved when the global motion compensated frames are used. The existing camera motion estimation methods for global motion compensation have a large amount of computations in common. In this paper, we propose a simple global motion estimation algorithm that consists of linear equations without any repetition. The algorithm uses information .of symmetric points in the frame of the video sequence. The discriminant conditions to distinguish regions belonging to distant view from foreground in the frame are presented. Only for the distant view satisfying the discriminant conditions, the linear equations for the panning, tilting, and zooming parameters are applied. From the experimental results using the MPEG test sequences, we can confirm that the proposed algorithm estimates correct global motion parameters. Moreover the real-time capability of the proposed technique can be applicable to many MPEG-4 and MPEG-7 related areas.

• Journal of Astronomy and Space Sciences
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• v.20 no.4
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• pp.351-358
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• 2003

The global stability of the attitude motion of a spin-stabilized space vehicle is investigated by performing numerical experiment. In the previous study, a stationary solution and a particular resonant condition for a given model were found by using analytical method but failed to represent the system stability over parameter values near and off the stationary points. Accordingly, as an extension of the previous work, this study performs numerical experiment to investigate the stability of the system across the parameter space and determines stable and unstable regions of the design parameters of the system.

• Journal of IKEEE
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• v.19 no.2
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• pp.244-253
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• 2015

Please This paper presents method of video stabilization based on detection and adaptive motion smoothing filtering of undesirable motion. The proposed algorithm consists of two stages: the detection of undesirable motion and smoothing filtering of detected undesired motion. To incorporate desired properties into the motion smoothing process, the local maximum and the local minimum are defined in a set composed of the parameters of accumulative global motion. Using the local information, the constraints on detecting undesirable motions are defined. Based on these constraints, the alpha parameter of the alpha-trimmed means filter is adjusted, so that the degree of motion smoothing in the reconstructed video sequence is controlled. The experimental results demonstrated the capability of the proposed algorithm.

• IEIE Transactions on Smart Processing and Computing
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• v.1 no.2
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• pp.78-87
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• 2012

In this paper, we address the tracking problem caused by camera motion and rolling shutter effects associated with CMOS sensors in consumer handheld cameras, such as mobile cameras, digital cameras, and digital camcorders. A modified particle filtering method is proposed for simultaneously tracking objects and compensating for the effects of camera motion. The proposed method uses an elastic registration algorithm (ER) that considers the global affine motion as well as the brightness and contrast between images, assuming that camera motion results in an affine transform of the image between two successive frames. By assuming that the camera motion is modeled globally by an affine transform, only the global affine model instead of the local model was considered. Only the brightness parameter was used in intensity variation. The contrast parameters used in the original ER algorithm were ignored because the change in illumination is small enough between temporally adjacent frames. The proposed particle filtering consists of the following four steps: (i) prediction step, (ii) compensating prediction state error based on camera motion estimation, (iii) update step and (iv) re-sampling step. A larger number of particles are needed when camera motion generates a prediction state error of an object at the prediction step. The proposed method robustly tracks the object of interest by compensating for the prediction state error using the affine motion model estimated from ER. Experimental results show that the proposed method outperforms the conventional particle filter, and can track moving objects robustly in consumer handheld imaging devices.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.2
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• pp.160-168
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• 2001

Change detection using difference picture has been used to detect the location of moving targets and to track them. This method needs the assumption of static camera, and the global motion compensation is required in case of a moving camera. This paper suggests a method for finding a minimum bounding rectangles(MBR) of moving targets in the image sequences using moving region detection, especially with a moving camera. If the global motion parameter is inaccurately estimated, the estimated locations of targets will be accurate either To alleviate this problem, we introduce the concept of the confidence measure and achieve more accurate estimation of global motion. Experimental results show that the proposed method successfully removes background region and extracts MBRs of the targets. Even with a moving camera, the new global motion estimation algorithm performs more precise]y and it reduces the background compensation errors of change detection.