Fast and Accurate Motion Estimation Algorithm By Adaptive Search Range and Shape Selection

Abstract

This paper presents a fast and accurate motion estimation algorithm. To obtain accurate motion vectors while minimizing computational complexity, we adjust the search range for each frame and each block to suit the motion level of the video. An appropriate search range for each frame is determined on the basis of motion vectors and prediction errors obtained for the previous frame. At each block, the search range is determined on the basis of the search range of its frame and of the motion vector values of all adjacent blocks for which those values have already been obtained. With our algorithm, since narrow search ranges are chosen for areas in which little motion occurs, computational complexity can be reduced without degrading estimation accuracy. Since wide search ranges are chosen for areas of significant motion, good video-quality encoding can be maintained. In the encoding of an SDTV size video, the addition of range adjustment results in a reduction in the computational complexity of motion estimation of roughly 65%, while maintaining the same video quality.

Computation-constrained dynamic search range control for real-time video encoder

“…Moreover, as discussed in Section 2, the predicted search range is proportional to the PMV deviation according to Eqs. (12) and (14). Hence, we can derive that, the computational complexity Ψ is approximately proportional to the square of the PMV deviation θ.…”

“…Get the lower and upper bounds for the predicted search range Step 4.4: Compute the predicted search range S i;j k ð Þ with the hitting probability threshold Λ TH by Eq. (14), and to maintain a limited computing requirement for current BPU, S i;j k ð Þ is clipped within the bound Ψ À 1 ε 2 ½ ; Ψ À 1t i;j k ð Þ Â Ã according Eq. (29)…”

“…Xu [13] improved the algorithm proposed in [12] to make it more suitable for H.264/AVC [2]. Yamada [14] presented a two-stage SR modification algorithm that limits the SR by the MVs of neighboring blocks as well as the prediction error of the corresponding block in the reference frame. Zhang [15] determined the SR based on the frame complexity measured by the degree of motion activity at frame level.…”

“…in which searching points are mainly determined by the search window, SR reduction algorithms are another way to reduce the computational complexity of ME. Dynamic search range (DSR) algorithms have been proposed by researchers [12][13][14][15][16][17][18][19][20][21] recently. The proposed DSR algorithm dynamically adjusts the SR for each Macroblock (MB) according to the information given by previously encoded syntax element.…”

Motion consistency based motion estimation for H.264/AVC

“…Many fast motion estimation algorithms have been proposed. Some strive to reduce the computational complexity by dynamically adjusting the search range [3], [4], [5], [6]. In * : author of correspondence.…”