This article presents an overview of the recent standardization activities for point cloud compression (PCC). A point cloud is a 3D data representation used in diverse applications associated with immersive media including virtual/augmented reality, immersive telepresence, autonomous driving and cultural heritage archival. The international standard body for media compression, also known as the Motion Picture Experts Group (MPEG), is planning to release in 2020 two PCC standard specifications: video-based PCC (V-CC) and geometry-based PCC (G-PCC). V-PCC and G-PCC will be part of the ISO/IEC 23090 series on the coded representation of immersive media content. In this paper, we provide a detailed description of both codec algorithms and their coding performances. Moreover, we will also discuss certain unique aspects of point cloud compression.
We present a new preprocessing technique for two-dimensional compression of surface electromyographic (S-EMG) signals, based on correlation sorting. We show that the JPEG2000 coding system (originally designed for compression of still images) and the H.264/AVC encoder (video compression algorithm operating in intraframe mode) can be used for compression of S-EMG signals. We compare the performance of these two off-the-shelf image compression algorithms for S-EMG compression, with and without the proposed preprocessing step. Compression of both isotonic and isometric contraction S-EMG signals is evaluated. The proposed methods were compared with other S-EMG compression algorithms from the literature.
This paper proposes a new way to store/transmit information using a Colored QR Code structure. Instead of using only black and white modules, the proposed code is designed to employ 5 different RGB colors (red, green, blue, black and white), which enables twice as much storage capacity compared to traditional binary QR Codes. Reed-Solomon error-correcting code with a theoretical correction capability of 38.41% is also applied. In our experiments, each Colored QR Code in the test set is printed, scanned using a 3.2 megapixel digital camera and decoded. We show that the proposed scheme can consistently decode 1024 bits of information stored on a 1.3 cm × 1.3 cm printed area.
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