This paper presents a face detection and recognition system utilizing a Raspberry Pi computer that is built on a predefined framework. The theoretical section of this article shows several techniques ...that can be used for face detection, including Haar cascades, Histograms of Oriented Gradients, Support Vector Machine and Deep Learning Methods. The paper also provides examples of some commonly used face recognition techniques, including Fisherfaces, Eigenfaces, Histogram of Local Binary Patterns, SIFT and SURF descriptor-based methods and Deep Learning Methods. The practical aspect of this paper demonstrates use of a Raspberry Pi computer, along with supplementary tools and software, to detect and recognize faces using a pre-defined dataset.
In this paper we will present a new dynamic point cloud compression based on different projection types and bit depth, combined with the surface reconstruction algorithm and video compression for ...obtained geometry and texture maps. Texture maps have been compressed after creating Voronoi diagrams. Used video compression is specific for geometry (FFV1) and texture (H.265/HEVC). Decompressed point clouds are reconstructed using a Poisson surface reconstruction algorithm. Comparison with the original point clouds was performed using point-to-point and point-to-plane measures. Comprehensive experiments show better performance for some projection maps: cylindrical, Miller and Mercator projections.
In this paper we present a novel no-reference video quality measure, NR-FFM (no-reference frame-freezing measure), designed to estimate quality degradations caused by frame freezing of streamed ...video. The performance of the measure was evaluated using 40 degraded video sequences from the laboratory for image and video engineering (LIVE) mobile database. Proposed quality measure can be used in different scenarios such as mobile video transmission by itself or in combination with other quality measures. These two types of applications were presented and studied together with considerations on relevant normalization issues. The results showed promising correlation values between the user assigned quality and the estimated quality scores.
This article describes an empirical exploration on the effect of information loss affecting compressed representations of dynamic point clouds on the subjective quality of the reconstructed point ...clouds. The study involved compressing a set of test dynamic point clouds using the MPEG V-PCC (Video-based Point Cloud Compression) codec at 5 different levels of compression and applying simulated packet losses with three packet loss rates (0.5%, 1% and 2%) to the V-PCC sub-bitstreams prior to decoding and reconstructing the dynamic point clouds. The recovered dynamic point clouds qualities were then assessed by human observers in experiments conducted at two research laboratories in Croatia and Portugal, to collect MOS (Mean Opinion Score) values. These scores were subject to a set of statistical analyses to measure the degree of correlation of the data from the two laboratories, as well as the degree of correlation between the MOS values and a selection of objective quality measures, while taking into account compression level and packet loss rates. The subjective quality measures considered, all of the full-reference type, included point cloud specific measures, as well as others adapted from image and video quality measures. In the case of image-based quality measures, FSIM (Feature Similarity index), MSE (Mean Squared Error), and SSIM (Structural Similarity index) yielded the highest correlation with subjective scores in both laboratories, while PCQM (Point Cloud Quality Metric) showed the highest correlation among all point cloud-specific objective measures. The study showed that even 0.5% packet loss rates reduce the decoded point clouds subjective quality by more than 1 to 1.5 MOS scale units, pointing out the need to adequately protect the bitstreams against losses. The results also showed that the degradations in V-PCC occupancy and geometry sub-bitstreams have significantly higher (negative) impact on decoded point cloud subjective quality than degradations of the attribute sub-bitstream.
This paper presents a summary of recent progress in compression, subjective assessment and objective quality measures of point cloud representations of three dimensional visual information. Different ...existing point cloud datasets, as well as discusses the protocols that have been proposed to evaluate the subjective quality of point cloud data. Several geometry and attribute point cloud data objective quality measures are also presented and described. A case study on the evaluation of subjective quality of point clouds in two laboratories is presented. Six original point clouds degraded with G-PCC and V-PCC point cloud compression and five degradation levels were subjectively evaluated, showing high inter-laboratory correlation. Furthermore, performance of several geometry-based objective quality measures applied to the same data are described, concluding that the highest correlation with subjective scores is obtained using point-to-plane measures. Finally, several current challenges and future research directions on point clouds compression and quality evaluation are discussed.
This paper presents a research study on the subjective assessment of 3D video quality using a newly constructed 3D video database (3DVCL@FER). This database consists of 8 original 3D video sequences, ...each degraded with 22 different degradation types, including degradations specific to stereoscopic systems. The subjective assessment was done with the support of a purpose-built easily customizable grade collection platform and conducted in two research laboratories, in Croatia and Portugal. Subjective scores for quality, depth and comfort were collected and DMOS (Difference Mean Opinion Score) values were calculated. Different objective measures (for image, 3D image, 2D video and 3D video) were separately compared with DMOS values for quality, depth and comfort. The 3D video grade-annotated database described is publicly accessible and can be used in research-related activities like assessment of existing objective measures, using the entire database or parts of it, and construction of new objective measures specific to 3D video degradations. The system presented can also be used to collect and compare subjective quality grades originating from different sites to study the effect of different observation conditions and observer/graders populations on the DMOS quality values for 3D video depth and comfort.
In this paper we present new image quality database VCL@FER (
http://www.vcl.fer.hr/quality/
) which consists of four degradation types, 6 levels of each degradation and 23 different images (552 ...degraded images). It can be used in objective image quality evaluation, as well as to develop and test new image quality measures. Results for six commonly used full reference objective quality measures are compared using newly developed image database, as well as 6 other image databases.
VCL@FER baza slika nova je baza slika (http://www.vcl.fer.hr/quality/) koja se sastoji od 4 vrste izobličenja, 6 razina svakog izobličenja i 23 različite slike (ukupno 552 izobličene slike). Baza ...slika može se koristiti za usporedbu različitih objektivnih mjera kvalitete slike, kao i za razvoj novih objektivnih mjera. Uporabom nove baze te još šest dostupnih baza slika provedena je usporedba šest relevantnih objektivnih mjere kvalitete slike.
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