Seongwan Kim

Fast PU Skip and Split Termination Algorithm for HEVC Intra Prediction

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

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.

Face detection using multi-modal features

In this paper, propose efficient methods for reducing false detection rate in face detection procedure when images apply face recognition and face entertainment from web or personal photo. Previous detection methods focused on accurate face detection. So, false detection rate makes a problem when put to practical use. This problem can overcome to use additional information when face detection. Proper information is color. But real color-RGB information is not adequate for face detection. Because RGB information is sensitive to light variations. Thus need to transfer coordination properly to use. Transferred channels are defined with genetic algorithm. After that make a model of facial skin color to score face candidate is real face or not. Propose method can dramatic reduce false detection rate when face detection procedure.

Tracking and Classification of In-Air Hand Gesture Based on Thermal Guided Joint Filter

The research on hand gestures has attracted many image processing-related studies, as it intuitively conveys the intention of a human as it pertains to motional meaning. Various sensors have been used to exploit the advantages of different modalities for the extraction of important information conveyed by the hand gesture of a user. Although many works have focused on learning the benefits of thermal information from thermal cameras, most have focused on face recognition or human body detection, rather than hand gesture recognition. Additionally, the majority of the works that take advantage of multiple modalities (e.g., the combination of a thermal sensor and a visual sensor), usually adopting simple fusion approaches between the two modalities. As both thermal sensors and visual sensors have their own shortcomings and strengths, we propose a novel joint filter-based hand gesture recognition method to simultaneously exploit the strengths and compensate the shortcomings of each. Our study is motivated by the investigation of the mutual supplementation between thermal and visual information in low feature level for the consistent representation of a hand in the presence of varying lighting conditions. Accordingly, our proposed method leverages the thermal sensor’s stability against luminance and the visual sensors textural detail, while complementing the low resolution and halo effect of thermal sensors and the weakness against illumination of visual sensors. A conventional region tracking method and a deep convolutional neural network have been leveraged to track the trajectory of a hand gesture and to recognize the hand gesture, respectively. Our experimental results show stability in recognizing a hand gesture against varying lighting conditions based on the contribution of the joint kernels of spatial adjacency and thermal range similarity.

Fast intermode decision algorithm based on general and local residual complexity in H.264/AVC

The state-of-the-art video coding standard H.264/AVC achieves significant coding performance by adopting variable block sizes for motion estimation (ME) and mode decision. However, this technique brings out high computational complexity since the optimal mode is determined by exhaustively performing rate-distortion optimization (RDO) on each coding mode with different block sizes. In this paper, the fast intermode decision algorithm is proposed to reduce the computational complexity. Based on the high correlation between the residual error of ME and the optimal block size, general residual complexity (GRC) and local residual complexity (LRC) are defined. According to MB activity evaluated on GRC and LRC, candidate intermodes are determined and RDO processes are only performed on selected intermodes. The experimental results demonstrate that the proposed algorithm achieves time saving by 63% on average with negligible degradation of coding efficiency.

Reversible watermarking with localization for biometric images

In this paper, we propose a novel reversible data hiding algorithm, which can recover the original image if it is deemed authentic or detect the block-wise malicious manipulation if it is classified as manipulated. We explore the strong spatial correlation of neighboring pixels in digital images to achieve very high embedding capacity and keep the distortion low. Also, this technique provides cryptographic strength when verifying image integrity because the probability of making undetectable modifications to the image is directly related to a secure cryptographic element, such as a hash function. The algorithm has been successfully applied to a wide range of images, including commonly used images, biometric images, texture images, and aerial images. Experimental results and performance comparison with other reversible data hiding schemes are presented to demonstrate the validity of the proposed algorithm.

SSIM-based distortion metric for film grain noise in HEVC

In video coding, the sum of squared differences (SSD) is traditionally used for rate-distortion optimization (RDO). However, SSD has been known that has low correlation on subjective quality. In particular, film grain noise (FGN)-synthesized video sequence is a very good example of subjective quality degradation with SSD-based RDO. Therefore, structural similarity (SSIM) has been considered for RDO owing to its simplicity and high correlation with subjective quality. The SSIM metric was not designed to be used for previous RDO framework; additional processing, such as content analysis or adaptive Lagrangian multipliers, was required in previous studies. Based on analyzing cases of degradation in SSIM-based coding, this study proposes a novel SSIM-like distortion measure. In this paper, two objectives are considered. First one is FGN-synthesized video coding using the SSIM-like distortion measure to preserve noise pattern. Seconds, the proposed metric is designed for direct application in previously developed RDO frameworks without scene-analysis-based RDO. The experimental results demonstrate that the proposed method reduces erroneous prediction blocks and the Bjøntegaard delta rate by 67.46% on average compared to original SSIM-based RDO for FGN-synthesized video sequences. The results show the proposed metric is effective for film grain noise in similar bit rate, compared to a high-efficiency video coding test model (HM16.6) and the original SSIM metric.

Low-delay stream switch method for real-time transfer protocol

With wide spread of smartphones and high speed mobile communication technology, mobile broadcasting market is growing rapidly. Bit stream change during Video-on-Demand service causes large delay of video and audio playback, which makes user inconvenience. To avoid large delay, a method for low-delay stream switch is proposed and implemented on Android platform. Experimental result shows 72.71ms of stream change time on average when bit stream change occurred.