Intra coding plays a crucial role in the High Efficiency Video Coding (HEVC) standard. It provides the higher coding efficiency than the previous standard, H.264/Advanced Video Coding. The block partitioning in HEVC supports quad-tree-based coding unit (CU) structure from size $64 \times 64$ to $8 \times 8$ . The new technique provides better performances on one hand, whereas on the other hand it also increases the coding complexity. In this paper, a novel fast algorithm is proposed for the CU size decision in intra coding. Both the global and local edge complexities in horizontal, vertical, 45° diagonal, and 135° diagonal directions are proposed and used to decide the partitioning of a CU. Coupled with handling its four sub-CUs in the same way, a CU is decided to be split, nonsplit, or undetermined for each depth. Compared with the reference software HM10.0, the encoding time is reduced by $\sim 52$ % on average, with $\sim 0.8$ % Bjontegaard Distortion-rate increasing and reasonable peak signal-to-noise ratio losses.

A Fast CU Size Decision Algorithm for the HEVC Intra Encoder

Recently, a new video coding standard, High Efficiency Video Coding (HEVC), has shown greatly improved coding efficiency by adopting hierarchical structures of coding unit (CU), prediction unit (PU), and transform unit (TU). To best achieve the coding efficiency, the best combinations of CU, PU, and TU must be found in the sense of the minimum rate-distortion (R-D) costs. Owing to this, a large computational complexity occurs. Among these CU, PU, and TU, the determination of CU sizes most significantly affects the R-D performance of HEVC encoders, which causes large computational costs in operation with PU and TU size determinations. In spite of recent works in the complexity reduction of HEVC encoders, most of the research has focused on the complexity reduction with fast CU split in intra slice coding and with early TU split in both intra and inter slice. In this paper, we propose a fast and an efficient CU encoding scheme based on the spatiotemporal encoding parameters of HEVC encoders, which consists of an improved early CU SKIP detection method and a fast CU split decision method. For the current CU block under encoding, the proposed scheme utilizes sample-adaptive-offset parameters as the spatial encoding parameter to estimate the texture complexity that affects the CU partition. In addition, the motion vectors, TU size, and coded block flag information are used as the temporal encoding parameters to estimate the temporal complexity that also affects the CU partition. The proposed scheme effectively utilizes the spatiotemporal encoding parameters that are the byproducts during the encoding process of HEVC without additionally required computation. The proposed novel fast CU encoding scheme significantly reduces the total encoding time with negligible RD-performance loss. The experimental results show that the proposed scheme achieves the total encoding time savings of average 49.6% and 42.7% only with average 1.4% and 1.0% bit-rate losses for various test sequences under random access and low delay B conditions, respectively. The proposed scheme has an advantage on the implementation for parallel processing in pipeline structures of HEVC encoders due to its independency with neighboring CU blocks.

A Novel Fast CU Encoding Scheme Based on Spatiotemporal Encoding Parameters for HEVC Inter Coding

The latest video coding standard High Efficiency Video Coding (HEVC) achieves about a 50% bit-rate reduction compared with H.264/AVC under the same perceptual video quality. For intra coding, a coding unit (CU) is recursively divided into a quadtree-based structure from the largest CU $64 \times 64$ to the smallest CU $8 \times 8$ . Also, up to 35 intra-prediction modes are allowed. These two techniques improve the intra-coding performance significantly. However, the encoding complexity increases several times compared with H.264/AVC intra coding. In this paper, fast intra-mode decision and CU size decision are proposed to reduce the complexity of HEVC intra coding while maintaining the rate-distortion (RD) performance. For fast intra-mode decision, a gradient-based method is proposed to reduce the candidate modes for rough mode decision and RD optimization. For fast CU size decision, the homogenous CUs are early terminated first. Then two linear support vector machines that employ the depth difference and HAD cost ratio (and RD cost ratio) as features are proposed to perform the decisions of early CU split and early CU termination for the rest of the CUs. Experimental results show that the proposed fast intra-coding algorithm achieves about a 54% encoding time reduction on average with only a 0.7% BD-rate increase for the HEVC reference software HM 14.0 under all-intra configuration.

Fast Intra-Mode and CU Size Decision for HEVC

Fast reference frame selection based on content similarity for low complexity HEVC encoder

Screen content coding (SCC) has evolved into the extension of the High Efficiency Video Coding (HEVC). Low-latency, real-time transport between devices in the form of screen content video is becoming popular in many applications. However, the complexity of encoder is still very high for intra prediction in HEVC-based SCC. This paper proposes a fast intra prediction method based on content property analysis for HEVC-based SCC. First, coding units (CUs) are classified into natural content CUs (NCCUs) and screen content CUs (SCCUs), based on the statistic characteristics of the content. For NCCUs, the newly adopted prediction modes, including intra block copy mode and palette mode are skipped, if the DC or PLANR mode is the best mode, after testing the traditional intra prediction rough modes. In addition, the quadtree partition process is also terminated due to the homogeneous and smooth block usually chooses a large size CU. For SCCUs, a rank-based decision strategy is introduced to terminate the splitting process of current CU. For all CUs, the bit per pixel of current CU is used to make a CU size decision. Meanwhile, the depth information of neighboring CUs and co-located CU are utilized to further improve the performance. Experimental results show that the proposed algorithm can save 44.92% encoding time on average with negligible loss of video quality.

Fast Intra Prediction Based on Content Property Analysis for Low Complexity HEVC-Based Screen Content Coding

High Efficiency Video Coding (HEVC) employs a coding unit (CU), prediction unit (PU), and transform unit (TU) based on the quadtree coding tree unit (CTU) structure to improve coding efficiency. However, the computational complexity increases greatly because the rate-distortion (RD) optimization process should be performed for all CUs, PUs, and TUs to obtain the optimal CTU partition. In this paper, a fast CU size decision algorithm is proposed to reduce the encoder complexity of HEVC. Based on the statistical analysis, three approaches with SKIP mode decision (SMD), CU skip estimation (CUSE), and early CU termination (ECUT) are considered. In SMD, it is determined that the remaining modes except for SKIP mode are preformed or not. CUSE and ECUT determine that larger CU sizes and smaller CU sizes are coded or not, respectively. Thresholds for SMD, CUSE, and ECUT are designed based on Bayes’ rule with a complexity factor. Update process is performed to estimate the statistical parameters for SMD, CUSE, and ECUT considering the characteristic of RD cost. The experimental results demonstrate that the proposed CU size decision algorithm significantly reduces computational complexity by 69% on average with 2.99% Bjontegaard difference bitrate (BDBR) increase for random access. The complexity reduction and BDBR increase for low delay are 68% and 2.46%, respectively. The experimental results also show that our proposed scheme performs well for various characteristic of sequences and outperforms the two previous state-of-the-art works.

A Fast CU Size Decision Algorithm for HEVC

High Efficiency Video Coding (HEVC) is developed for next-generation video coding, which achieves significant improvements in coding efficiency compared with H.264/Advanced Video Coding by adopting various tools including a quadtree-based block partitioning structure. However, this causes high encoding complexity for exhaustive rate-distortion (RD) cost computation of the extended prediction unit (PU) searching. In this paper, a fast PU skip and split termination algorithm is proposed. The proposed method consists of three algorithms: 1) early skip; 2) PU skip; and 3) PU split termination. The early skip algorithm allows immediate skipping of the RD cost computation for large PUs according to the neighboring PUs. Based on Bayes’s rule, the PU skip algorithm allows skipping of the full RD cost computation, and the split termination algorithm terminates further PU splitting using the RD cost of rough mode decision (RMD). The decision parameter for the PU skip and the split termination is presented as the ratio of the RMD RD costs between the current PU and the spatially adjacent or upper depth PU. The simulation results show that the proposed algorithm achieves a saving of 53.52% encoding time while maintaining almost the same RD performances as the HEVC reference software.

Fast PU Skip and Split Termination Algorithm for HEVC Intra Prediction

The H.264/AVC standard achieves high compression performance compared to existing video coding standards by employing the rate distortion optimization (RDO) technique. All possible combinations of modes are calculated to find the minimum rate distortion cost which results in significant computational complexity. In this paper, we propose a fast block size and mode decision method for intra prediction, which can effectively reduce computational burden. For fast block size decision, intra16x16 is selectively searched based on the homogeneity of inner-8x8 block of macroblock (MB). For fast mode decision, the search of intra16x16 and intra4x4 prediction modes is restricted by the similarity of the reference pixels. Moreover, by considering the similarities of the upper reference pixels and left reference pixels separately, considerable reduction of computational complexity is achieved. The results of simulations demonstrate maxima of 79% and 77% average time savings with negligible loss in PSNRY and bitrate.

Fast block size and mode decision algorithm for intra prediction in H.264/AVC

The performance of face recognition systems has much been burdened by head pose and light variations. To solve the head pose variation problem, 3D face modeling systems and 3D head pose estimation methods have been suggested. In addition, thermal information is considered to solution of the light variation problem recently. Pose and light problems are separative problems in numerous approaches, generally. In this paper, we propose Thermal 3D face modeling system which includes shape, texture, and thermal information. Proposed system consists of a projector, visual and thermal cameras. To solve correspondence problem between 3 sensors, we use 3-view geometry.

Thermal 3D Face Modeling System

Detecting and tracking fingertips are significant techniques for recognizing hand gestures. Many patterns and skin color information are used to extract and trace features [1, 2]. However, to find correct shapes is difficult and there is limitation to express the diversity of models. In this paper, we describe a method of detecting and tracking fingertips based on Active Shape Models (ASMs) and an ellipse equation. ASM is an effective tool to obtain features of a specific object in images by using a trained model. The ellipse equation helps a template follow the object without skin color information. We show how well fingertips are extracted and traced through some experiments.

Kyungmin Lim

Papers

A Fast CU Size Decision Algorithm for HEVC

Fast PU Skip and Split Termination Algorithm for HEVC Intra Prediction

Fast block size and mode decision algorithm for intra prediction in H.264/AVC

Thermal 3D Face Modeling System

Fingertips detection and tracking based on active shape models and an ellipse