METHOD OF DECIDING PRESENCE OF GLOBAL MOTION BY USING 2-DIMENSIONAL TRANSLATIONAL MOTION VECTORS AND LINEAR REGRESSION

Abstract: The present invention is to provide a method of deciding the existence of global motion which can reduce the computation amount according to the motion compensation by not performing the global motion compensation and improve the coding efficiency at the time of application of image coding in case where the global motion does not exist, by deciding the presence of global motion by performing a test for global motion model adequacy after estimating the global motion by utilizing 2-D translational motion vectors and linear regression.

Description: METHOD OF DECIDING PRESENCE OF GLOBAL MOTION BY USING 2-DIMENSIONAL TRANSLATIONAL MOTION VECTORS AND LINEAR REGRESSION BACKGROUND OF THE INVENTION Field of the Invention The present invention relates to a method of deciding presence of global motion which decides the presence of global motion in successive images. Information Disclosure Statement Conventional global motion estimation and compensation estimates global motion on the assumption that the global motion always exists and performs global motion compensation by using the estimated global motion. However, there is a problem in the conventional method that even in the case where global motion does not exist but local motion only exists, the conventional method performs global motion compensation so that it reduces the coding efficiency and requires a lot of unnecessary computation in global motion compensation process. Therefore, in case of performing global motion compensation for moving image sequences, a method of deciding necessity of global motion compensation according to a result after deciding in advance the existence of global motion is necessary since there is not always the global motion. SUMMARY OF THE INVENTION The object of the present invention invented to solve the problems described above is to provide a method of deciding the existence of global motion which can reduce the computation amount according to the motion compensation by not performing the global motion compensation and improve the coding efficiency at the time of application of image coding in case where the global motion does not exist, by deciding the presence of global motion by performing a test for global motion model adequacy after estimating the global motion by utilizing 2-D translational motion vectors and a linear regression. The present invention to accomplish the object described above provides a method of deciding the presence of global motion which is applied to a global motion estimation and compensation apparatus comprising a first step of estimating a motion vector of a central point of each block from successive images; a second step of estimating a global motion parameter from the motion vectors by using linear regression; and a third step of deciding the presence of global motion by performing global motion model adequacy test for the motion vectors and global motion parameters. BRIEF DESCRIPTION OF THE DRAWINGS For fuller understanding of the nature and object of the invention, reference should be had to the following detailed description taken in conjunction with the accompanying drawings in which: Fig. 1 is a constructional block diagram of a global motion estimation and compensation apparatus for successive images to which the present invention is applied; and Fig. 2 is a flowchart of the method of deciding the presence of global motion according to the present invention. Similar reference characters refer to similar parts in the several views of the drawings. DETAILED DESCRIPTION OF THE EMBODIMENTS Below is given a detailed description of an embodiment according to the present invention with reference to the accompanying drawings. Fig. 1 is a constructional block diagram of a global motion estimation and compensation apparatus for successive images to which the present invention is applied and is a constructional block diagram of a motion estimation and compensation part of a video coding system. First, a successive image receiving section 100 receives the successive images, and a global motion estimating section 101 receives a previous image and current image from the successive image receiving section 100 and estimates the global motion. That is, a global motion model is assumed and the global motion is estimated by using one of various global motion estimation methods. A global motion presence deciding section 102 decides the presence of global motion by using the estimated motion parameter. A global motion compensating section 103 performs global motion compensation according to the result of decision of global motion presence according to the present invention. That is, in case of presence of global motion, global motion compensation is performed from the previous image frame by using the global motion parameter so as to remove the global motion existing between the current frame and the previous frame. Then, a local motion existing between the current frame and the global motion compensated image is estimated and compensated. In case of absence of global motion, the global motion compensation is not performed and only the local motion existing between the previous frame and current frame is estimated and compensated. Fig. 2 is a flowchart of a method of deciding the presence of global motion according to the present invention. The present invention reduces the computation according to the motion compensation by not performing the global motion compensation and improves the coding efficiency at the time of application of image coding in case where the global motion does not exist, by deciding the present of global motion by performing a test for model adequacy of global motion after estimating the global motion by utilizing 2-D translational motion vectors and linear regression. First, the successive images are received at step 201 and 2-dimensional translational motion vector {v x (x„ y , v } (x„ y^} of the central point {x„ y,) of each block is obtained from the received successive images at step 202. That is, the motion vector of each block or the motion vector of central point of block is obtained by using the 2-D translational motion vector estimation method such as Block Matching Algorithm. In case where the motion vector of block is estimated, the estimated motion vector of block is taken as the motion vector of central point (x„ y,) of block. Thereafter, the global motion parameter a is estimated from the estimated 2-D translational motion vector {v x (x„ v,), v y (x„ _y,)} by using the line.ar regression. There can be various models such as affine model, perspective model and quadratic model as the global motion model. The method of deciding the presence of global motion according to the present invention can be applied to any global motion model, however, and embodiment of the present invention will be explained based on affine motion model such as equation 1 described below. [Equation 1] v r (r, y) - x - x' ≡ β , ♦ a x * ay v , (χ, y) - y - y' ≡ « 4 ♦ a x * ay Here, (x', y 1 ) represents 2-D image-space coordinate before camera motion occurs, and (x, y) represents 2-D image-space coordinate after camera motion occurs. {v x (x, y), y)} represents theoretical motion vector at point (x, y). Estimation of global motion parameters estimates the parameters such that the motion vector {v x (x h y,), v } (x„ y } of central point of each block computed according to equation 1 best matches the motion vector {v x (x h yi), v y .(x y,)} of central point of each block estimated according to 2-D translational motion estimation method. Assuming that the distribution of noise is Gaussian distribution where all the average is zero except the vectors due to minor local motions, least square error estimation becomes optimum estimator having unbiased and minimum variance which is unbiased in the sense of maximum likelihood according to the Gauss-Markov theorem. Therefore, the global motion parameters are obtained such that error function such as equation 2 described below becomes minimum. [Equation 2] £ 0) Here, N represents the number of all of motion vectors used in global motion parameter estimation. Since the local motion due to a moving object besides the global motion due to a camera can exist in the successive images, the motion vector due to local motion influences the global motion estimation in case of estimating the global motion by using the motion vectors of all block centers in the image. Therefore, the global motion parameters are estimated at step 203 by iteratively performing the global motion estimation and local motion removal (removal of outlier) until the global motion parameters converge. Thereafter, the necessity of global motion compensation is decided at step 204 via the global motion model accuracy test from the estimated 2-D translational motion vectors and estimated global motion parameters. Since the global motion parameters according to the present invention is estimated from the estimated translational motion vector {v (x,, y,), v (x„ y,)} by using the linear regression, if the degree to which the global motion of image is well modeled by the given motion parameter is known, the given motion parameters can be taken as a reference for deciding whether the global motion exists in the successive images. That is, in case where the global motion is dominant in the motion of the successive images, it can be said that the estimated global motion parameters well describe the global motion in the image. If to the contrary only the local motion exists in the image, the estimated global motion parameters have no physical meaning. Based on such fact, the presence of global motion in the successive images can be decided by using the global motion mode adequacy test by using the estimated 2-D translational motion vector {v x (x„ >,), v y (x„ -,)} and the motion vector {v x (x„ y \ y (x„ )} computed from the global motion parameter. The global motion presence decision according to the present invention is performed by introducing the concept of coefficient of multiple determination R 2 which is frequently used in the linear regression analysis, the method being as follows. First, average motion vector (v γ , Ϋ such as the following equation 3 is obtained from the 2-D translational motion vector {v x (x„ y , v } (x„ y )} of central point (x„ y of each block estimated by using 2- D translational motion estimation method. [Equation 3] Here, N represents the number of motion vectors used in estimation of final global motion parameters except the motion vectors due to local motion. Thereafter, an error sum {S mx , S vvy } between the estimated 2-D translational motion vector {v (x„ y , v y (x„ >,)} and average motion vector (v„ V y ) of the estimated 2-D translational motion vector {v x (x„ y , v y (x„ _y,)} is computed by the following equation 4. [Equation 4] s w* - Σ v r (*, , y,) - x , S wy - ∑ ^ ( y (*, , y,) - T y f Then, .an error sum {SS Ex , SS Ey } between the translated 2-D translational motion vector {v x (x„ y , v (x„ y } and the motion vector y,), v } (x„ y } computed by equation 1 from the global motion parameter obtained as an optimum solution is computed by following equation 5. [Equation 5] SS E * - Σ ,.! [v r (*, , y,) - r (*, , y, )? , SS Ey - ∑ [Λ [v y (*, , y,) - ζ, ( , , y t )f Thereafter, coefficient of multiple determination {R x , R y 2 } is obtained by the following equation 6 from {S n , S n ) and {SS E , SS Ey } . [Equation 6] Λ » . i _ ^£ , Λ ' i . ^Z 5 wx y S my Coefficient of multiple determination {R 2 , Ry) can be used as a measure for reduction of variability of motion vector {v (x„ y v y (x„ y } obtained from the estimated motion parameter. That is, in case where the global motion is dominant, since the magnitude of the error sum {.S^ x , SS Ey } of the optimum solution becomes relatively small, coefficient of multiple determination {R x , R y 2 } is increased. As can be seen from equation 6 described above, coefficient of multiple determination {R x , R } 2 } has a range of 0 < R x , R y ≤ 1. Finally, the presence of global motion is decided as follows from coefficient of multiple determination {Ry , R y 2 } . Maximum value R 2 of coefficient of multiple determination {R x , R 2 } is obtained by the following equation 7. [Equation 7] R ≡ maximun [R χ , R y ] When R 2 exceeds a given threshold value, it is decided that the global motion exists, and the global motion compensation is performed. When R 2 is smaller than the given threshold value, it is decided that the global motion does not exist, and the global motion compensation is not performed. The present invention described above has an effect that it can not only prevent the degradation of coding efficiency due to unconditional global motion compensation but also reduce the amount of computation by not perform the global motion compensation in case where the global motion does not performing the global motion compensation in case where the global motion does not exist by deciding in advance the presence of global motion. The foregoing description, although described in its preferred embodiment with a certain degree of particularity, is only illustrative of the principles of the present invention. It is to be understood that the present invention is not to be limited to the preferred embodiments disclosed and illustrated herein. Accordingly, all expedient variations that may be made within the scope and the spirit of the present invention are to be encompassed as further embodiments of the present invention.

Claims: What is claimed is: 1. A method of deciding the prsence of global motion which is applied to a global motion estimation and compensation apparatus comprising the steps of: a first step of estimating a motion vector of each block from successive images; a second step of estimating a global motion parameter from said motion vector by using linear regression; and a third step of deciding the presence of global motion by performing global motion model adequacy test for said motion vector and global motion parameter. 2. The method as claimed in claim 1, further comprising a fourth step of performing global motion compensation existing between current frame and previous frame by performing global motion model adequest test, and of not performing grobal motion compensation for which there is no grobal motion between the current frame and the previous frame by performing a model adequate test for the grobal motion model. 3. The method as claimed in claim 1 or 2, wherein said decision whether grobal motion exists or does not exist between the current frame and the previous frame is made by comparing maximum value of said coefficients of miltiple determination with a predefined threshold, wherein grobal motion does exist in case where said maximum value is larger than said predetermined threshold value and grobal motion does not exist in case when said maximum value is smaller than said predetermined threshold value.

Inventors: AHN CHIE TEUK, CHOI JAE GARK, KIM MUN CHURL, LEE MYOUNG HO, YI JONG WON, AHN, CHIE, TEUK, CHOI, JAE, GARK, KIM, MUN, CHURL, LEE, MYOUNG, HO, YI, JONG, WON
Applicants: AHN CHIE TEUK, CHOI JAE GARK, KIM MUN CHURL, KOREA ELECTRONICS TELECOMM, LEE MYOUNG HO, YI JONG WON, AHN, CHIE, TEUK, CHOI, JAE, GARK, ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE, KIM, MUN, CHURL, LEE, MYOUNG, HO, YI, JONG, WON
Application year: 1998
Main classification: G06T7
IPC codes: G06T7, G06T15, H04N7