Content-Aware Fast Motion Estimation Algorithm for IoT Based Multimedia Service

Abstract

Various applications based on IoT real-time multimedia are under the spotlight. To implement real-time multimedia service, motion estimation in video compression service has a high computational complexity. In this paper, an efficient motion search method based on content awareness is proposed consisting of three steps. The first step is motion classification using the center position cost distribution. The second step is calculation of a predictor based motion classification. The third step is setting the arm size of the search pattern based on adaptive use of the distance between the predictor and the center position. Experimental results show that the proposed algorithm achieves speed-up factors of up to 48.57% and 16.03%, on average, with good bitrate performance, compared with fast integer-pel and fractional-pel motion estimation for H.264/AVC (UMHexagonS), and an enhanced predictive zonal search for single and multiple frame motion estimation (EPZS) methods using JM 18.5, respectively. In addition, the proposed algorithm achieves a speed-up factor of up to 42.61%, on average, with negligible bitrate degradation, compared with the TZ search motion estimation algorithm for the multiview video coding (TZS) method on HM 10.0.