A point cloud visualizes information by placing a voxel with a color value and a position value in a three-dimensional space. Since a point cloud uses hundreds of thousands or millions of points to visualize information, a large number of bits is needed compared to existing 2D media. Therefore, it is essential to compress point data for transmission and storage. The Moving Picture Expert Group (MPEG) is developing a point cloud compression method based on 2D video that takes advantage of the benefits of coding efficiency and the wide adaption of video codecs by various industries. This compression method is called videobased point cloud compression (V-PCC). Generally, video codecs use a compression method that employs a block matching algorithm. Currently, V-PCC is conducted using 2D video codecs, which means that motion information used by V-PCC is obtained from 2D video sequences. Thus, this 2D-based motion information limits the characterization of the motion in terms of 3D-points, which is also disadvantageous to compression efficiency. In this paper, we propose a method for estimating and compensating the motion in terms of a 3D object when compressing a dynamic object point cloud using a conventional video codec. The proposed 3D motion estimation and compensation technology showed higher gain overall in terms of BD-rate and was proven to effectively compress 3D point cloud content on the basis of 3D motion. INDEX TERMS Video-based point cloud compression, 3D motion search, 3D motion estimation, compression of vector information.
β-Ga2O3 is a highly promising semiconductor for a deep ultraviolet emitter owing to its wide bandgap, which significantly varies in the range of 4.49 eV to 4.74 eV due to its optical trirefringence in the monoclinic crystal structure (C2h). However, dominant photoluminescence (PL) emissions in β-Ga2O3 occur far below the bandgap, where the underlying PL mechanism has been under intense debate. In order to address this issue, we monitored the most intense PL peaks at 3.0 eV and 3.5 eV at room temperature by employing both linear and nonlinear absorption spectroscopy. The PL of β-Ga2O3 was found to be highly polarized along the (102) direction regardless of input polarization, and to be essentially the same for one-photon absorption (1PA), two-photon absorption (2PA), and three-photon absorption (3PA). However, absorption polarization dependence is quite distinct for 1PA, 2PA, and 3PA, as theoretically explained by optical selection rules for C2h symmetry. Based on the input-output method, 2PA and 3PA coefficients were determined to be 𝛽 = 3.45 cm GW -1 and 𝛾 = 0.013 cm 3 GW -2 at the excitation wavelength of 460 nm and 550 nm, respectively. These values are several times higher than theoretical values predicted by two-band models, indicating that β-Ga2O3 possesses strong optical nonlinearity with high polarization contrast. The absorption power dependences for 1PA, 2PA, and 3PA indicate that optical excitation is essentially excitonic, but bound to Ga vacancies (3.0 eV) and O vacancies (3.5 eV), which is different from the so-called self-trapped exciton based on the polaron model. Our main thesis is also clearly supported by the dependence of the PL shape on the excitation depth as probed by 2PA depth scan. This implies that densities for the Ga vacancy and the O vacancy vary differently as a function of depth from the excitation surface. A broad set of highly asymmetric optical properties clarified in our work is critical for the understanding of this wide-gap semiconductor and its potential use for ultraviolet sources especially when band-edge emission is realized.
Fast binary dilation and erosion algorithms using run‐length encoding (RLE) are proposed. RLE is an alternative way of representing a binary image using a run, which is a sequence of ‘1’ pixels. First, we derive the run‐based representation of dilation and erosion and then present the full steps of the proposed algorithms in detail.
From stitching video sequences point of view, an existing image stitching technique may have limitations on object movement or loss in the stitched video sequence due to the different parallax of the individual video sequences. Also, an existing image stitching technique have higher computational complexity and have matching accuracy limitations in obtaining descriptors for many factors. Therefore, this paper proposes an edge-based weight minimum error seam method in order to overcome the limitations caused by parallax and video stitching and trigonometric ratio-based image match algorithm in order to reduce computational complexity and insensitivity to rotation, illumination, image size, or resolution.
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