Cloud-based deployment of content production and broadcast workflows has continued to disrupt the industry after the pandemic. The key tools required for unlocking cloud workflows, e.g., transcoding, metadata parsing, and streaming playback, are increasingly commoditized. However, as video traffic continues to increase there is a need to consider tools which offer opportunities for further bitrate/quality gains as well as those which facilitate cloud deployment. In this paper we consider preprocessing, rate/distortion optimisation and cloud cost prediction tools which are only just emerging from the research community. These tools are posed as part of the per-clip optimisation approach to transcoding which has been adopted by large streaming media processing entities but has yet to be made more widely available for the industry.

With video streaming making up 80% of the global internet bandwidth, the need to deliver high-quality video at low bitrate, combined with the high complexity of modern codecs, has led to the idea of a per-clip optimisation approach in transcoding. In this paper, we revisit the Lagrangian multiplier parameter, which is at the core of rate-distortion optimisation. Currently, video encoders use prediction models to set this parameter but these models are agnostic to the video at hand. We explore the gains that could be achieved using a per-clip direct-search optimisation of the Lagrangian multiplier parameter. We evaluate this optimisation framework on a much larger corpus of videos than that has been attempted by previous research. Our results show that per-clip optimisation of the Lagrangian multiplier leads to BD-Rate average improvements of 1.87% for x265 across a 10 k clip corpus of modern videos, and up to 25% in a single clip. Average improvements of 0.69% are reported for libaom-av1 on a subset of 100 clips. However, we show that a per-clip, per-frame-type optimisation of λ for libaom-av1 can increase these average gains to 2.5% and up to 14.9% on a single clip. Our optimisation scheme requires about 50–250 additional encodes per-clip but we show that significant speed-up can be made using proxy videos in the optimisation. These computational gains (of up to ×200) incur a slight loss to BD-Rate improvement because the optimisation is conducted at lower resolutions. Overall, this paper highlights the value of re-examining the estimation of the Lagrangian multiplier in modern codecs as there are significant gains still available without changing the tools used in the standards.

Since the adoption of VP9 by Netflix in 2016, royalty-free coding standards continued to gain prominence through the activities of the AOMedia consortium. AV1, the latest open source standard, is now widely supported. In the early years after standardisation, HDR video tends to be under served in open source encoders for a variety of reasons including the relatively small amount of true HDR content being broadcast and the challenges in RD optimisation with that material. AV1 codec optimisation has been ongoing since 2020 including consideration of the computational load. In this paper, we explore the idea of direct optimisation of the Lagrangian λ parameter used in the rate control of the encoders to estimate the optimal Rate-Distortion trade-off achievable for a High Dynamic Range signalled video clip. We show that by adjusting the Lagrange multiplier in the RD optimisation process on a frame-hierarchy basis, we are able to increase the Bjontegaard difference rate gains by more than 3.98× on average without visually affecting the quality.

In the past ten years there have been significant developments in optimization of transcoding parameters on a per-clip rather than per-genre basis. In our recent work we have presented per-clip optimization for the Lagrangian multiplier in Rate controlled compression, which yielded BD-Rate improvements of approximately 2% across a corpus of videos using HEVC. However, in a video streaming application, the focus is on optimizing the rate/distortion tradeoff at a particular bitrate and not on average across a range of performance. We observed in previous work that a particular multiplier might give BD rate improvements over a certain range of bitrates, but not the entire range. Using different parameters across the range would improve gains overall. Therefore here we present a framework for choosing the best Lagrangian multiplier on a per-operating point basis across a range of bitrates. In effect, we are trying to find the para-optimal gain across bitrate and distortion for a single clip. In the experiments presented we employ direct optimization techniques to estimate this Lagrangian parameter path approximately 2,000 video clips. The clips are primarily from the YouTube-UGC dataset. We optimize both for bitrate savings as well as distortion metrics (PSNR, SSIM).

The majority of internet traffic is video content. This drives the demand for video compression to deliver high quality video at low target bitrates. Optimising the parameters of a video codec for a specific video clip (per-clip optimisation) has been shown to yield significant bitrate savings. In previous work we have shown that per-clip optimisation of the Lagrangian multiplier leads to up to 24% BD-Rate improvement. A key component of these algorithms is modeling the R-D characteristic across the appropriate bitrate range. This is computationally heavy as it usually involves repeated video encodes of the high resolution material at different parameter settings. This work focuses on reducing this computational load by deploying a NN operating on lower bandwidth features. Our system achieves BD-Rate improvement in approximately 90% of a large corpus with comparable results to previous work in direct optimisation.

Optimising the parameters of a video codec for a specific video clip has been shown to yield significant bitrate savings. In particular, per-clip optimisation of the Lagrangian multiplier in Rate controlled compression, has led to BD-Rate improvements of up to 20% using HEVC. Unfortunately, this was computationally expensive as it required multiple measurement of rate distortion curves which meant in excess of fifty video encodes were used to generate that level of savings. This work focuses on reducing the computational cost of repeated video encodes by using a lower resolution clip as a proxy. Features extracted from the low resolution clip are then used to learn the mapping to an optimal Lagrange Multiplier for the original resolution clip. In addition to reducing the computational cost and encode time by using lower resolution clips, we also investigate the use of older, but faster codecs such as H.264 to create proxies. This work shows the computational load is reduced by up to 22 times using 144p proxies, and more than 60% of the possible gain at the original resolution is achieved. Our tests are based on the YouTube UGC dataset, using the same computational platform; hence our results are based on a practical instance of the adaptive bitrate encoding problem. Further improvements are possible, by optimising the placement and sparsity of operating points required for the rate distortion curves. Our contribution is to improve the computational cost of per clip optimisation with the Lagrangian multiplier, while maintaining BD-Rate improvement.

This paper provides an improvement to automated cricket highlight identification from full broadcasts. Further refinement is provided through semi- automated user verification. This visual result is synchronized with an automated text extraction process. The visual result was successfully extracted at a rate of 97.5% using the ORB function. With user validation a false detection rate of 0% was realized. The metadata from the commentary was then successfully extracted and combined with the visual results to allow for easy searching of the highlight video using any search field.

The majority of internet traffic is video content. This drives the demand for video compression in order to deliver high quality video at low target bitrates. This paper investigates the impact of adjusting the rate distortion equation on compression performance. An constant of proportionality, k, is used to modify the Lagrange multiplier used in H.265 (HEVC). Direct optimisation methods are deployed to maximise BD-Rate improvement for a particular clip. This leads to up to 21 we use a more realistic corpus of material provided by YouTube. The results show that direct optimisation using BD-rate as the objective function can lead to further gains in bitrate savings that are not available with previous approaches.

Motion estimation is a key component of any modern video codec. Our understanding of motion and the estimation of motion from video has come a very long way since 2000. More than 135 different algorithms have been recently reviewed by Scharstein et al http://vision.middlebury.edu/flow/. These new algorithms differ markedly from Block Matching which has been the mainstay of video compression for some time. This paper presents comparisons of H.264 and MP4 compression using different motion estimation methods. In so doing we present as well methods for adapting pre-computed motion fields for use within a codec. We do not observe significant gains to be had with the methods chosen w.r.t. Rate Distortion tradeoffs but the results reflect a significantly more complex interrelationship between motion and compression than would be expected. There remains much more to be done to improve the coverage of this comparison to the emerging standards but these initial results show that there is value in these explorations.

The amount of data is exploding, and by all estimations will continue its exponential growth. This has led to an increased demand for engineers and data scientists. However, courses imparting crucial ideas from data design, administration and maintenance to data analytics and knowledge discovery remain under-subscribed due to perceived difficulty, low interest and motivation. This motivation can be represented by three constructs: interest in the topic, personal control and difficulty of the exercise. Role-playing games (RPGs) have been proven to stimulate students interest in analysis and problem solving when faced with varying tasks. This paper investigates the integration of specific game-based elements and pop-culture references into course delivery and assessment to boost interest and learner motivation in an elective postgraduate database systems course at The University of the West Indies. The experimental setup for assessment of students' progress in this course uses an experience point (XP) level-based system adapted from popular RPGs. To further stimulate interest, pop-culture references to specific animated series' and fantasy game genres are used. A student can choose to take one of multiple paths for their learning, representing different tools/platforms that can be used in implementation and analysis. Students can attempt more than one path for more experience and higher levels, although it is not expected. Completion of each path indicates formative “mastery” of the selected data science tool/platform. Summative assessments uses a “raid-party system” where students who have been encouraged along different paths are now asked to join together to 1. analyse given datasets and capture their findings in the format of an academic paper, and 2. build a complete database application for a particular scenario. Formative feedback is done in groups to leverage scaffolding. Measurement of the students' activity and interest is done using automatically generated activity logs from the online delivery course system as well as administration of an online electronic questionnaire. Both of these instruments are used to determine how effective this approach is in influencing students' interest and motivation. More than 5 times the historical enrollment numbers have been observed and initial results point to improvement in students' attitudes toward the content. This action research would be used to inform content delivery and further investigations would determine the impact on student performance.

This paper investigates the use of the Oriented Fast, Rotated Brief (ORB) method to automatically detect the most significant broadcast view associated with cricket broadcasts: the Bowler Run-up Sequence (BRS) for cricket highlight generation. This method is computationally less expensive than other methods proposed for BRS detection. It is shown here that only a single frame is required for training to produce acceptable results as compared to other BRS detection methods. The ORB method produced a BRS detection rate of 98.26% and false detection rate of 5.70% and average matching time of 0.059 seconds. The fast training and matching makes this ideal for real time generation of highlight sand the detection is robust to sequences with high camera motion.

This work investigates the effects of variations in skin-topology on the non-invasive measurement of blood glucose levels using an interdigital electrode. Several models of varying skin topologies were built and analysed within the COMSOL Multiphysics® 4.3 software environment. The deviations in blood glucose readings for the varying skin topologies were quantised. Finally the authors propose and model an alternative interdigital electrode structures. Variations in skin-topology can occur due to movement of the patient during readings and common variations in the skin surface from one person to the next or even different locations on the same person. Non-invasive measurement methods offer improved patient quality of care by reducing the pain and risk associated with testing.

Spectrum measurements are a crucial element of compliance enforcement in dynamic spectrum access (DSA) networks and for emerging interference limit policies such as harm claim thresholds. Such measurements should provide better spatio-temporal resolution than traditional compliance enforcement approaches for characterisation of spectrum usage. Using current techniques, even in distributed monitoring networks, monitoring nodes typically sense contiguous spectral bands, including sub-bands which may not be of interest. This can be energy inefficient, particularly for use in denser monitoring networks, such as those envisioned for DSA within the VHF and UHF bands. In this paper a knowledge-based, non-contiguous, multi-resolution sensing approach for characterization of spectrum occupancy is proposed for compliance enforcement networks. The knowledge framework is introduced for scenarios involving heterogeneous radio access technologies (RAT), and non-uniform spectral sampling using the Non-Uniform Fast Fourier Transform (NUFFT) is demonstrated. The performance of the proposed approach is compared to the typical contiguous sensing approach used in practice, using simulations. Results suggest that the proposed approach can decrease the number of computations required, which would improve energy efficiency for individual nodes in monitoring networks.

One challenge faced in the engineering education, is the need to imbue both technical competence and critical thinking skills within the bounds of academic program delivery. While technical competence can be built and assessed using structured and/or quantitative exercises, critical thinking is a skill that is both difficult to cultivate and to assess. Critical thinking involves the possession of both an expert mental model as well as the ability to leverage this model in various tasks. In engineering education, these tasks include making and justifying design choices, system optimization, and predicting system performance. Prior work, by one of the authors, explored the role of graphic organizers in the development of student's mental models. This paper describes action research underway, to explore the use of the argument map, as a structured means of leveraging mental models to promote critical thinking. In this paper, interactive smallgroup tasks based on argument maps are presented, and outputs generated by the initial cohort of undergraduate senior learners on these tasks are examined for evidence of critical thinking. These items form the basis of a longer-term longitudinal study in which the most effective means of deploying argument maps for promoting critical thinking will be examined.

This paper reviews a number of regional and extra-regional robotics initiatives. Each initiative was reviewed to determine different age groups of students, the goals of stake-holders involved in enabling an initiative, and the benchmarks for success of each initiative. The review has informed the design of an integrated intervention for Teacher Training initiated by the Trinidad and Tobago Ministry of Education Curriculum Development Division. The intervention is based on a problem-solving process, and targets teachers of students in the early secondary age group. Empowering and encouraging older student volunteers to support teachers allows for the increased longevity of the robotics initiative. The potential to foster wider student interest in STEM subjects within the Caribbean remains to be explored.

This paper explores whether engaging embedded electronic systems students in the creation of, as opposed to simply the use of, lab equipment improves their motivation to practice, and thereby their ability to acquire, discipline-specific skills. The specific piece of laboratory equipment considered is the Microchip In Circuit Debugger, inclusive of header, for PIC16F mid-range micro-controllers. A printed circuit board related teaching activity guided students through design of the ICD header (both 2011/12 and 2013/14), and physical assembly of a pre-designed ICD unit (2011/12 only). Three student cohorts subsequently used the in-house ICDs. Increased availability of units allowed each student to take the equipment outside of the lab and conduct studies at their convenience. The impact of the intervention was measured through the use of a survey; the survey instrument and response summaries are presented. Deliberate use of equipment construction as teaching activity could be an innovative way to improve skills acquisition by leveraging student motivation. Follow-up work will establish whether such activities yield reduction in time to minimal skill levels, and/or an improvement in final skill levels.