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Jang, Euee S.,Preda, Marius,Mammou, Khaled,Tourapis, Alexis M.,Kim, Jungsun,Graziosi, Danillo B.,Rhyu, Sungryeul,Budagavi, Madhukar IEEE 2019 IEEE signal processing magazine Vol.36 No.3
<P>The widespread adoption of new 3D sensor and authoring technologies has made it possible to capture 3D scenes and models in real time with decent visual quality. As an example, Microsoft's Kinect and Apple's PrimeSense technology are now being used in a wide variety of interactive 3D mobile applications, including gaming and augmented reality applications. The latest smartphones are equipped with multiple cameras, which can be readily used to generate depth images. Some of the latest smartphones also include depth-ranging sensors that can be used for 3D model generation. Light-based detection and ranging (lidar) technologies are yet another field where 3D depth acquisition is important. Realtime 3D scenery detection and ranging has become an important issue for the emerging field of autonomous navigation and driving applications.</P>
Jang, Euee Seon,Chong, Jong-Wha IEEE 2017 IEEE TRANSACTIONS ON IMAGE PROCESSING - Vol.26 No.10
<P>This correspondence is to address the corrections to the published paper titled “An efficient adaptive binary arithmetic coder based on logarithmic domain”.</P>
Palette-based Color Attribute Compression for Point Cloud Data
( Li Cui ),( Euee S. Jang ) 한국인터넷정보학회 2019 KSII Transactions on Internet and Information Syst Vol.13 No.6
Point cloud is widely used in 3D applications due to the recent advancement of 3D data acquisition technology. Polygonal mesh-based compression has been dominant since it can replace many points sharing a surface with a set of vertices with mesh structure. Recent point cloud-based applications demand more point-based interactivity, which makes point cloud compression (PCC) becomes more attractive than 3D mesh compression. Interestingly, an exploration activity has been started to explore the feasibility of PCC standard in MPEG. In this paper, a new color attribute compression method is presented for point cloud data. The proposed method utilizes the spatial redundancy among color attribute data to construct a color palette. The color palette is constructed by using K-means clustering method and each color data in point cloud is represented by the index of its similar color in palette. To further improve the compression efficiency, the spatial redundancy between the indices of neighboring colors is also removed by marking them using a flag bit. Experimental results show that the proposed method achieves a better improvement of RD performance compared with that of the MPEG PCC reference software.
Intra-picture Block-matching Method for Codebook-based Texture Compression
( Li Cui ),( Euee S. Jang ) 한국인터넷정보학회 2016 KSII Transactions on Internet and Information Syst Vol.10 No.10
In this paper, an efficient texture compression method is proposed for fast rendering, which exploits the spatial correlation among blocks through intra-picture block matching. Texture mapping is widely used to enhance the visual quality of results in real-time rendering applications. For fast texture mapping, it is necessary to identify an effective trade-off between compression efficiency and computational complexity. The conventional compression methods utilized for image processing (e.g., JPEG) provide high compression efficiency while resulting in high complexity. Thus, low complexity methods, such as ETC1, are often used in real-time rendering applications. Although these methods can achieve low complexity, the compression efficiency is still lower than that of JPEG. To solve this problem, we propose a texture compression method by reducing the spatial redundancy between blocks in order to achieve the better compression performance than ETC1 while maintaining complexity that is lower than that of JPEG. Experimental results show that the proposed method achieves better compression efficiency than ETC1, and the decoding time is significantly reduced compared to JPEG while similar to ETC1.
MPEG-5 EVC Encoder Improvement for V-PCC
Tianyu Dong,Euee S. Jang 한국방송·미디어공학회 2021 한국방송공학회 학술발표대회 논문집 Vol.2021 No.6
In this paper, we proposed an improved method on the picture order of coding (POC) of MPEG-5 Essential video Coding (EVC) encoder to support a short intra period for Video-based Point Cloud Compression (V-PCC). As a codec-agnostically designed standard, V-PCC claimed to be able to work with a lot of codecs. Current EVC test model software shows that the baseline profile could not provide appropriate POC calculation. The proposed method offers a solution to this POC-related problem and provides up to 44.6% coding grains for EVC based V-PCC.
Comments on “Fast Motion Estimation Based on Content Property for Low-Complexity H.265/HEVC Encoder”
Park, Sang-hyo,Jang, Euee S. [Institute of Electrical and Electronics Engineers 2017 IEEE transactions on broadcasting Vol.63 No.4
<P>In this paper, we provide comments on the recent paper by Pan <I>et al.</I> that proposed an initial search point-based motion estimation skipping (ISP-MES) method. We found some discrepancies of the proposed method and its experimental results, especially in setting the ISPs. In this paper, we clarify these issues and, as a result, provide an enhanced results from the work of Pan <I>et al.</I></P>
Leveraging Parallel Computing in Modern Video Coding Standards
Choi, Kiho,Jang, Euee S. IEEE 2012 IEEE multimedia Vol.19 No.3
<P>Video coding has always been a computationally intensive process. Although dramatic improvements in coding efficiency have been realized in recent years, the algorithms have become increasingly complex and there is a broader recognition that it is necessary to realize the capabilities of multicore processors. This article discusses how recent trends in parallel computing have influenced the design of modern video coding standards. Specifically, the authors discuss how the High Efficiency Video Coding (HEVC) standard, which is being jointly developed by ISO/IEC JTC1/SC29 WG11 (MPEG) and ITU-T SH16/Q.6 (VCEG), is looking at ways to implement the co-exploration between algorithm and architecture (CEAA) approach.</P>