Luís Cruz

Objective quality prediction model for lost frames in 3D video over TS

This paper proposes an objective model to predict the quality of lost frames in 3D video streams. The model is based only on header information from three different packet-layer levels: Network Abstraction Layer (NAL), Packetised Elementary Streams (PES) and Transport Stream (TS). Transmission errors leading to undecodable TS packets are assumed to result in frame loss. The proposed method estimates the size of the lost frames, which is used as a model parameter to predict their objective quality measured as the Structural Similarity Index Metric (SSIM). The results show that SSIM of missing stereoscopic frames in 3D coded video can be predicted with Root Mean Square Error (RMSE) accuracy of about 0.1 and Pearson correlation coefficient of 0.8, taking the SSIM of uncorrupted frames as reference. It is concluded that the proposed model is capable of estimating the SSIM quite accurately using only the lost frames estimated sizes.

Complexity reduction of depth intra coding for 3D video extension of HEVC

Three dimensional (3D) video technology, systems and applications such as 3D television and freeviewpoint television (FTV) broadcasts require efficient encoding of video information. To fill that need a 3D video extension of High Efficiency Video Coding standard, called 3D-HEVC, is being developed. This extension is based on Multiview Video plus Depth (MVD) format, which associates a depth information to each texture frame of each view. This paper presents a method to accelerate the intra coding of these depth maps to reduce the 3D-HEVC computational complexity. The proposed algorithm exploits the edge orientation of the depth blocks to reduce the number of modes to be evaluated in the intra mode decision. In addition, the correlation between the Planar mode choice and the most probable modes (MPMs) selected is also exploited, to accelerate the depth intra coding. The experimental results show that the proposed algorithm achieves an average complexity reduction of 15% on depth information encoding, with a small degradation in encoding efficiency (BD-rate increase of 0.16% on average).

HEVC intra mode decision acceleration based on tree depth levels relationship

The new High Efficiency Video Coding (HEVC) standard is achieving higher encoding efficiency when compared to its predecessors such as H.264/AVC. One of the factors responsible to this improvement is the intra prediction method, which introduces a larger number of prediction directions resulting in an enhanced rate-distortion (RD) performance at the cost of a higher computational complexity. This paper proposes an algorithm to accelerate the intra mode decision, reducing the complexity of intra coding. The acceleration procedure takes into account the edge direction information and explores the correlation of intra modes across levels of the HEVC hierarchical tree structure. Experimental results show that the proposed algorithm provides a decrease of up to 40.82% in the HEVC intra prediction processing time, with a small degradation in encoding efficiency (BD-PSNR loss of 0.1 dB on average).

Fast mode selection algorithm based on texture analysis for 3D-HEVC intra prediction

The increasing availability of 3D video systems and applications has attracted more consumers for 3D viewing experiences and, consequently, the demand for storage and transmission of 3D video content is growing. An interesting alternative for this need is the transmission of 3D video based on the Multiview Video plus Depth (MVD) format. The upcoming 3D High Efficiency Video Coding (3D-HEVC) standard will adopt this format, which associates a depth map to each texture frame. This paper presents a fast mode decision algorithm, which analyses the texture frames and depth maps to detect the edge orientation of the prediction units (PUs), optimizing the intra prediction process and reducing the 3D-HEVC computational complexity. The experimental results show that the proposed algorithm achieves an average processing time reduction of 26.2%, with a small degradation in encoding efficiency (BD-rate increase of 0.3% on average).

Greening transportation and parking at University of Coimbra

Purpose This paper aims to explore the potential contribution of integrated traffic and parking management strategies to ensure more rational use of available parking spaces and to reduce fuel consumption and greenhouse gas emissions by commuters traveling to the University of Coimbra (UC) main campus. Design/methodology/approach An integrated modelling approach is used, including the characterization of supply and demand for parking and public transport, the creation and implementation of a survey to campus users and a life-cycle approach to assess six transportation and parking strategy scenarios. Findings This comprehensive analysis demonstrates the importance of integrated management measures to greening commuters’ transportation and parking within a University campus, identifying and quantifying opportunities for successfully making the transitions toward a more sustainable future, namely, increasing well-being and reducing environmental impact. Practical implications Results demonstrate that effective control of illegal parking and different forms of modal shift toward public transportation may contribute to important reductions in environmental impacts. Social implications Local population reveals willingness to participate in collective efforts to tackle traffic and parking problems, challenging authorities to take action and empowering ever more people to engage in such cathartic changes. Originality/value This comprehensive approach is highly valuable for the management of parking and traffic within the UC campus, providing innovative lessons on the social and environmental impacts that would result from this policy approach to urban areas (e.g. historical centers) facing the typical problems of a carbon society, such as traffic congestion, non-regulated parking and intensive car use.

Encoding time control system for HEVC based on Rate-Distortion-Complexity analysis

The improved compression efficiency of High Efficiency Video Coding (HEVC) comes with large increases in computational complexity, which has been lately dealt by researchers with complexity reduction and scaling methods. However, encoding time control at frame or Group of Pictures (GOP) level is still an open issue that must be investigated. In this work, a Rate-Distortion-Complexity analysis is performed upon a set of configurations that have been created based on findings and techniques of previous works. The proposed control system uses the best 27 configurations to adjust the encoding time per GOP and yields encoding time reductions of up to 84.5% with an average difference between target and encoding times of 4.1%.

Benchmark of state of the art objective measures for 3D stereoscopic video quality assessment on the Nantes database

In this work we present a study on the performance of existing state of the art 2D objective image and video quality measures, tested on the new 3D stereoscopic video NAMA3DS1-COSPAD1 database. Different image and video quality measures have been tested on test material affected by different types of degradations. Results show that in some cases, image quality measures give better results than video quality measures. This paradoxical result means that more effort should be devoted to designing new 3D video quality assessment measures. The results presented and accompanying discussion can be used to motivate and guide future research directed towards definition of effective new 3D stereoscopic video quality measures.

Computational complexity control for HEVC based on coding tree spatio-temporal correlation

The High Efficiency Video Coding standard shows improved compression efficiency in comparison to previous standards at the cost of higher computational complexity. In this paper, a complexity control method for HEVC encoders based on the dynamic adjustment of the number of constrained coding treeblocks is proposed. The method limits the maximum tree depth used in the coding structures based on spatio-temporal correlation in order to decrease the number of evaluations performed in the Rate-Distortion Optimization process. Experimental results show that the proposed method is capable of maintaining the encoding time per frame under a pre-defined target, reaching computational complexity decreases of up to 50% at the cost of an average BD-PSNR loss of 0.26 dB in the worst case scenario.

Four-step algorithm for early termination in HEVC inter-frame prediction based on decision trees

The flexible encoding structures of High Efficiency Video Coding (HEVC) are the main responsible for the improvements of the standard in terms of compression efficiency in comparison to its predecessors. However, the flexibility provided by these structures is accompanied by high levels of computational complexity, since more options are considered in a Rate-Distortion (R-D) optimization scheme. In this paper, we propose a four-step early-termination method, which decides whether the inter mode decision should be halted without testing all possibilities. The method employs a set of decision trees, which are trained offline once, using information from unconstrained HEVC encoding runs. The resulting trees present a mode decision accuracy ranging from 97.6% to 99.4% with a negligible computational overhead. The method is capable of achieving an average computational complexity decrease of 49% at the cost of a very small Bjontegaard Delta (BD)-rate increase (0.58%).

No-reference lightweight estimation of 3D video objective quality

A no-reference (NR) method based on an artificial neural network (ANN) approach is proposed in this paper to estimate the objective quality of video-plus-depth streams subject to packet loss in depth data. A novel aspect of this method is the use of information only taken from packet headers, up to the network abstraction layer (NAL), requiring a very low complexity parsing of the compressed video streams. A maximum of seven packet-layer parameters were found to be enough to provide accurate objective quality estimates given by the structural similarity index (SSIM). The accuracy of the quality estimates, evaluated by comparison with the actual SSIM quality scores, is shown to be sufficiently high (e.g., Pearson Linear Correlation Coefficient over 0.92) for lightweight implementations of 3D video quality monitors at end-user receivers and also at network nodes.