A First Step Towards Synthesising Rubrics and Video for the Formative Assessment of Complex Skills

Abstract. The performance objectives used for the formative assessment of com- plex skills are generally set through text-based analytic rubrics[1]. Moreover, video modeling examples are a widely applied method of observational learning, providing students with context-rich modeling examples of complex skills that act as an analogy for problem solving [1]. The purpose of this theoretical paper is to synthesize the components of video modeling and rubrics to support the formative assessment of complex skills. Based on theory, we argue that application of the developed Video Enhanced Rubrics (VER) fosters learners’ development of mental models, quality of provided feedback by various actors and finally, the learners mastery of complex skills.

Viewbrics: Formative Assessment of Complex Skills with Video-Enhanced Rubrics (VER) in Dutch Secondary Education

To learn complex skills, like collaboration, learners need to acquire a concrete and consistent mental model of what it means to master this skill. If learners know their current mastery level and know their targeted mastery level, they can better determine their subsequent learning activities. Rubrics support learners in judging their skill performance as they provide textual descriptions of skills’ mastery levels with performance indicators for all constituent subskills. However, text-based rubrics have a limited capacity to support the formation of mental models with contextualized, time-related and observable behavioral aspects of a complex skill. This paper outlines the design of a study that intends to investigate the effect of rubrics with video modelling examples compared to text-based rubrics on skills acquisition and feedback provisioning. The hypothesis is that video-enhanced rubrics, compared to text based rubrics, will improve mental model formation of a complex skill and improve the feedback quality a learner receives (from e.g. teachers, peers) while practicing a skill, hence positively effecting final mastery of a skill.

Robust indoor speaker recognition in a network of audio and video sensors

Situational awareness is achieved naturally by the human senses of sight and hearing in combination. Automatic scene understanding aims at replicating this human ability using microphones and cameras in cooperation. In this paper, audio and video signals are fused and integrated at different levels of semantic abstractions. We detect and track a speaker who is relatively unconstrained, i.e., free to move indoors within an area larger than the comparable reported work, which is usually limited to round table meetings. The system is relatively simple: consisting of just 4 microphone pairs and a single camera. Results show that the overall multimodal tracker is more reliable than single modality systems, tolerating large occlusions and cross-talk. System evaluation is performed on both single and multi-modality tracking. The performance improvement given by the audio–video integration and fusion is quantified in terms of tracking precision and accuracy as well as speaker diarisation error rate and precision–recall (recognition). Improvements vs. the closest works are evaluated: 56% sound source localisation computational cost over an audio only system, 8% speaker diarisation error rate over an audio only speaker recognition unit and 36% on the precision–recall metric over an audio–video dominant speaker recognition method.

Video anomaly detection in real-time on a Power-Aware Heterogeneous Platform

FPGAs and GPUs are often used when real-time performance in video processing is required. An accelerated processor is chosen based on task-specific priorities (power consumption, processing time and detection accuracy), and this decision is normally made once at design time. All three characteristics are important, particularly in battery-powered systems. Here we propose a method for moving selection of processing platform from a single design-time choice to a continuous run time one.We implement Histogram of Oriented Gradients (HOG) detectors for cars and people and Mixture of Gaussians (MoG) motion detectors running across FPGA, GPU and CPU in a heterogeneous system. We use this to detect illegally parked vehicles in urban scenes. Power, time and accuracy information for each detector is characterised. An anomaly measure is assigned to each detected object based on its trajectory and location, when compared to learned contextual movement patterns. This drives processor and implementation selection, so that scenes with high behavioural anomalies are processed with faster but more power hungry implementations, but routine or static time periods are processed with power-optimised, less accurate, slower versions. Real-time performance is evaluated on video datasets including i-LIDS. Compared to power-optimised static selection, automatic dynamic implementation mapping is 10% more accurate but draws 12W extra power in our testbed desktop system.

Detection of frontal faces in video streams

[EN]This paper describes an approach for detection of frontal faces in real time (20-35Hz) for further processing. This approach makes use of a combination of previous detection tracking and color for selecting interest areas. On those areas, later facial features such as eyes, nose and mouth are searched based on geometric tests, appearance veri cation, temporal and spatial coherence. The system makes use of very simple techniques applied in a cascade approach, combined and coordinated with temporal information for improving performance. This module is a component of a complete system designed for detection, tracking and identi cation of individuals [1].

Panoramic Sea Happening (After Kantor): Video Installation

Panoramic Sea Happening (After Kantor) is a 7 minute durational film that reimagines part of Tadeusz Kantor's original sea happenings from 1967 in a landscape in which the sea has retreated. The conductor of Kantor’s original performance is replaced with a sound object cast adrift on a beach in Dungeness (UK). The object plays back the sound of the sea into the landscape, which was performed live and then filmed from three distinct angles. The first angle mimics the position of the conductor in Kantor’s original happening, facing outwards into the horizon of the beach and recalls the image in Kantor’s work of a human figure undertaking the absurd task of orchestrating the sound of a gigantic expanse of water. The second angle exposes the machine itself and the large cone that amplifies the sound, reinforcing the isolation of the object. The third angle reveals a decommissioned nuclear power station and sound objects used as a warning system for the power plant. Dungeness is a location where the sea has been retreating from the land, leaving traces of human activity through the disused boat winches, abandoned cabins and the decommissioned nuclear buildings. It is a place in which the footprint of the anthropocene is keenly felt. The sound object is intended to act as an anthropomorphic figure, ghosting the original conductor and offering the sound of the sea back into the landscape through a wide mouthpiece, echoing Kantor’s own load hailer in the original sequence of sea happenings. It speculates on Kantor's theory of the bio-object, which proposed a symbiotic relationship between the human and the nonhuman object in performance, as a possible instrument to access a form of geologic imagination. In this configuration, the human itself is absent, but is evoked through the objects left behind. The sound object, helpless in a red dingy, might be thought of as a co-conspirator with the viewer, enabling a looking back to the past in a landscape of an inevitable future. The work was originally commissioned by the University of Kent in collaboration with the Polish Cultural Institute for the Symposium Kantorbury Kantorbury in Canterbury (UK) to mark the 100 years since Tadeusz Kantor’s birth (15 - 19 September 2015). It should be projected and requires stereo speakers.

Pathfinder: a performance-game for the augmented drum-kit

Pathfinder is a performance-game for solo drummer, exploring the synergies between multiple contemporary creative practices. The work navigates between music composition, improvisation, projection/light art and game art. At its heart lies a bespoke electro-acoustic instrument, the augmented drum-kit, used not only to provide the sonic content of the work in real-time, but also as a highly expressive game controller that interacts with an instrument-specific game. The musical instrument offers a much wider range of expressive possibilities, control and tactile feedback in comparison to a traditional general-purpose game controller, and as a result it affords a more diverse and nuanced game play performance. Live electronics, lights, projections and the drum-kit all make up the performance-game’s universe, within which the performer has to explore, adapt, navigate and complete a journey.

Performance analysis in soccer: applications of player tracking technology

The aim of this thesis was threefold, firstly, to compare current player tracking technology in a single game of soccer. Secondly, to investigate the running requirements of elite women’s soccer, in particular the use and application of athlete tracking devices. Finally, how can game style be quantified and defined. Study One compared four different match analysis systems commonly used in both research and applied settings: video-based time-motion analysis, a semi-automated multiple camera based system, and two commercially available Global Positioning System (GPS) based player tracking systems at 1 Hertz (Hz) and 5 Hz respectively. A comparison was made between each of the systems when recording the same game. Total distance covered during the match for the four systems ranged from 10 830 ± 770 m (semi-automated multiple camera based system) to 9 510 ± 740m (video-based time-motion analysis). At running speeds categorised as high-intensity running (>15 km⋅h-1), the semi-automated multiple camera based system reported the highest distance of 2 650 ± 530 m with video-based time-motion analysis reporting the least amount of distance covered with 1 610 ± 370 m. At speeds considered to be sprinting (>20 km⋅h-1), the video-based time-motion analysis reported the highest value (420 ± 170 m) and 1 Hz GPS units the lowest value (230 ± 160 m). These results demonstrate there are differences in the determination of the absolute distances, and that comparison of results between match analysis systems should be made with caution. Currently, there is no criterion measure for these match analysis methods and as such it was not possible to determine if one system was more accurate than another. Study Two provided an opportunity to apply player-tracking technology (GPS) to measure activity profiles and determine the physical demands of Australian international level women soccer players. In four international women’s soccer games, data was collected on a total of 15 Australian women soccer players using a 5 Hz GPS based athlete tracking device. Results indicated that Australian women soccer players covered 9 140 ± 1 030 m during 90 min of play. The total distance covered by Australian women was less than the 10 300 m reportedly covered by female soccer players in the Danish First Division. However, there was no apparent difference in the estimated "#$%&', as measured by multi-stage shuttle tests, between these studies. This study suggests that contextual information, including the “game style” of both the team and opposition may influence physical performance in games. Study Three examined the effect the level of the opposition had on the physical output of Australian women soccer players. In total, 58 game files from 5 Hz athlete-tracking devices from 13 international matches were collected. These files were analysed to examine relationships between physical demands, represented by total distance covered, high intensity running (HIR) and distances covered sprinting, and the level of the opposition, as represented by the Fédération Internationale de Football Association (FIFA) ranking at the time of the match. Higher-ranking opponents elicited less high-speed running and greater low-speed activity compared to playing teams of similar or lower ranking. The results are important to coaches and practitioners in the preparation of players for international competition, and showed that the differing physical demands required were dependent on the level of the opponents. The results also highlighted the need for continued research in the area of integrating contextual information in team sports and demonstrated that soccer can be described as having dynamic and interactive systems. The influence of playing strategy, tactics and subsequently the overall game style was highlighted as playing a significant part in the physical demands of the players. Study Four explored the concept of game style in field sports such as soccer. The aim of this study was to provide an applied framework with suggested metrics for use by coaches, media, practitioners and sports scientists. Based on the findings of Studies 1- 3 and a systematic review of the relevant literature, a theoretical framework was developed to better understand how a team’s game style could be quantified. Soccer games can be broken into key moments of play, and for each of these moments we categorised metrics that provide insight to success or otherwise, to help quantify and measure different methods of playing styles. This study highlights that to date, there had been no clear definition of game style in team sports and as such a novel definition of game style is proposed that can be used by coaches, sport scientists, performance analysts, media and general public. Studies 1-3 outline four common methods of measuring the physical demands in soccer: video based time motion analysis, GPS at 1 Hz and at 5 Hz and semiautomated multiple camera based systems. As there are no semi-automated multiple camera based systems available in Australia, primarily due to cost and logistical reasons, GPS is widely accepted for use in team sports in tracking player movements in training and competition environments. This research identified that, although there are some limitations, GPS player-tracking technology may be a valuable tool in assessing running demands in soccer players and subsequently contribute to our understanding of game style. The results of the research undertaken also reinforce the differences between methods used to analyse player movement patterns in field sports such as soccer and demonstrate that the results from different systems such as GPS based athlete tracking devices and semi-automated multiple camera based systems cannot be used interchangeably. Indeed, the magnitude of measurement differences between methods suggests that significant measurement error is evident. This was apparent even when the same technologies are used which measure at different sampling rates, such as GPS systems using either 1 Hz or 5 Hz frequencies of measurement. It was also recognised that other factors influence how team sport athletes behave within an interactive system. These factors included the strength of the opposition and their style of play. In turn, these can impact the physical demands of players that change from game to game, and even within games depending on these contextual features. Finally, the concept of what is game style and how it might be measured was examined. Game style was defined as "the characteristic playing pattern demonstrated by a team during games. It will be regularly repeated in specific situational contexts such that measurement of variables reflecting game style will be relatively stable. Variables of importance are player and ball movements, interaction of players, and will generally involve elements of speed, time and space (location)".

Deep convolutional neural networks for semantic video object segmentation

In this thesis, we propose to infer pixel-level labelling in video by utilising only object category information, exploiting the intrinsic structure of video data. Our motivation is the observation that image-level labels are much more easily to be acquired than pixel-level labels, and it is natural to find a link between the image level recognition and pixel level classification in video data, which would transfer learned recognition models from one domain to the other one. To this end, this thesis proposes two domain adaptation approaches to adapt the deep convolutional neural network (CNN) image recognition model trained from labelled image data to the target domain exploiting both semantic evidence learned from CNN, and the intrinsic structures of unlabelled video data. Our proposed approaches explicitly model and compensate for the domain adaptation from the source domain to the target domain which in turn underpins a robust semantic object segmentation method for natural videos. We demonstrate the superior performance of our methods by presenting extensive evaluations on challenging datasets comparing with the state-of-the-art methods.

Efficient Image and Video Representations for Retrieval

Image (Video) retrieval is an interesting problem of retrieving images (videos) similar to the query. Images (Videos) are represented in an input (feature) space and similar images (videos) are obtained by finding nearest neighbors in the input representation space. Numerous input representations both in real valued and binary space have been proposed for conducting faster retrieval. In this thesis, we present techniques that obtain improved input representations for retrieval in both supervised and unsupervised settings for images and videos. Supervised retrieval is a well known problem of retrieving same class images of the query. We address the practical aspects of achieving faster retrieval with binary codes as input representations for the supervised setting in the first part, where binary codes are used as addresses into hash tables. In practice, using binary codes as addresses does not guarantee fast retrieval, as similar images are not mapped to the same binary code (address). We address this problem by presenting an efficient supervised hashing (binary encoding) method that aims to explicitly map all the images of the same class ideally to a unique binary code. We refer to the binary codes of the images as `Semantic Binary Codes' and the unique code for all same class images as `Class Binary Code'. We also propose a new class­ based Hamming metric that dramatically reduces the retrieval times for larger databases, where only hamming distance is computed to the class binary codes. We also propose a Deep semantic binary code model, by replacing the output layer of a popular convolutional Neural Network (AlexNet) with the class binary codes and show that the hashing functions learned in this way outperforms the state­ of ­the art, and at the same time provide fast retrieval times. In the second part, we also address the problem of supervised retrieval by taking into account the relationship between classes. For a given query image, we want to retrieve images that preserve the relative order i.e. we want to retrieve all same class images first and then, the related classes images before different class images. We learn such relationship aware binary codes by minimizing the similarity between inner product of the binary codes and the similarity between the classes. We calculate the similarity between classes using output embedding vectors, which are vector representations of classes. Our method deviates from the other supervised binary encoding schemes as it is the first to use output embeddings for learning hashing functions. We also introduce new performance metrics that take into account the related class retrieval results and show significant gains over the state­ of­ the art. High Dimensional descriptors like Fisher Vectors or Vector of Locally Aggregated Descriptors have shown to improve the performance of many computer vision applications including retrieval. In the third part, we will discuss an unsupervised technique for compressing high dimensional vectors into high dimensional binary codes, to reduce storage complexity. In this approach, we deviate from adopting traditional hyperplane hashing functions and instead learn hyperspherical hashing functions. The proposed method overcomes the computational challenges of directly applying the spherical hashing algorithm that is intractable for compressing high dimensional vectors. A practical hierarchical model that utilizes divide and conquer techniques using the Random Select and Adjust (RSA) procedure to compress such high dimensional vectors is presented. We show that our proposed high dimensional binary codes outperform the binary codes obtained using traditional hyperplane methods for higher compression ratios. In the last part of the thesis, we propose a retrieval based solution to the Zero shot event classification problem - a setting where no training videos are available for the event. To do this, we learn a generic set of concept detectors and represent both videos and query events in the concept space. We then compute similarity between the query event and the video in the concept space and videos similar to the query event are classified as the videos belonging to the event. We show that we significantly boost the performance using concept features from other modalities.

Correlations among behavior, performance and environment in broiler breeders using multivariate analysis

Animal welfare issues have received much attention not only to supply farmed animal requirements, but also to ethical and cultural public concerns. Daily collected information, as well as the systematic follow-up of production stages, produces important statistical data for production assessment and control, as well as for improvement possibilities. In this scenario, this research study analyzed behavioral, production, and environmental data using Main Component Multivariable Analysis, which correlated observed behaviors, recorded using video cameras and electronic identification, with performance parameters of female broiler breeders. The aim was to start building a system to support decision-making in broiler breeder housing, based on bird behavioral parameters. Birds were housed in an environmental chamber, with three pens with different controlled environments. Bird sensitivity to environmental conditions were indicated by their behaviors, stressing the importance of behavioral observations for modern poultry management. A strong association between performance parameters and the behavior at the nest, suggesting that this behavior may be used to predict productivity. The behaviors of ruffling feathers, opening wings, preening, and at the drinker were negatively correlated with environmental temperature, suggesting that the increase of in the frequency of these behaviors indicate improvement of thermal welfare.

Sleep and academic performance of Portuguese teenagers

Abstract: Sleep has numerous important functions in the body, such as consolidation of memory, concentration and learning. Changes in sleep cycles in adolescents lead to sleep deprivation with consequences to academic performance. Our research question was What are the sleep habits that influence school performance (study environment, study planning, study method, reading skills, motivation to study, overall school performance) in adolescents? We aimed to identify sleep habits predictors of the quality of school performance in adolescents. Research Methods: Crosssectional analytical study. Data were collected through a self-administered questionnaire with socio-demographic questions, sleep habits and school performance scale. The sample consisted of 380 students between 7th and 9th grade, with an average age of 13.56 ± 1.23 years in the school year 2011/2012, from a 2nd and 3rd Cycle Basic School of the municipality of Viseu, Portugal. Findings: School performance in adolescents was associated with better subjective quality of sleep (p=0.000), with longer sleep duration (p=0.000), with watching tv/video before sleep (p=0.000), with the habit of studying before bedtime (p=0.012), with no computer use (p=0.013) and with reading habits before bed (p=0.000). School performance was also associated with adolescents who reported not feeling sleepy during class. The teenagers who sleep more and better, and who watch tv/video, study, do not use computers, and who read before going to bed, have a better school performance.

Pathfinder. Performance at the Sonorities Festival of Contemporary Music 2016

Pathfinder (2016) is an audiovisual performance-game for a solo drummer,exploring the synergies between multiple contemporary creative practices.The work navigates between music composition, improvisation, projection/ light art and game art. At its heart lies a bespoke electro-acoustic instrument,the augmented drum-kit, used not only to provide the sonic content of the work in real-time, but also as a highly expressive game controller that interacts with an instrument-specific game. The musical instrument offers a much wider range of expressive possibilities, control and tactile feedback in comparison to a traditional general-purpose game controller, and as a result it affords a very diverse and nuanced gameplay performance. Live electronics, lights, projections and the drum-kit all make up the performance-game’s universe, within which the performer has to explore, adjust, navigate and complete a journey.

Applicazioni tecnologiche e nuovi metodi di valutazione della performance negli sport acquatici

Nello sport di alto livello l’uso della tecnologia ha raggiunto un ruolo di notevole importanza per l’analisi e la valutazione della prestazione. Negli ultimi anni sono emerse nuove tecnologie e sono migliorate quelle pre-esistenti (i.e. accelerometri, giroscopi e software per l’analisi video) in termini di campionamento, acquisizione dati, dimensione dei sensori che ha permesso la loro “indossabilità” e l’inserimento degli stessi all’interno degli attrezzi sportivi. La tecnologia è sempre stata al servizio degli atleti come strumento di supporto per raggiungere l’apice dei risultati sportivi. Per questo motivo la valutazione funzionale dell’atleta associata all’uso di tecnologie si pone lo scopo di valutare i miglioramenti degli atleti misurando la condizione fisica e/o la competenza tecnica di una determinata disciplina sportiva. L’obiettivo di questa tesi è studiare l’utilizzo delle applicazioni tecnologiche e individuare nuovi metodi di valutazione della performance in alcuni sport acquatici. La prima parte (capitoli 1-5), si concentra sulla tecnologia prototipale chiamata E-kayak e le varie applicazioni nel kayak di velocità. In questi lavori è stata verificata l’attendibilità dei dati forniti dal sistema E-kayak con i sistemi presenti in letteratura. Inoltre, sono stati indagati nuovi parametri utili a comprendere il modello di prestazione del paddler. La seconda parte (capitolo 6), si riferisce all’analisi cinematica della spinta verticale del pallanuotista, attraverso l’utilizzo della video analisi 2D, per l’individuazione delle relazioni Forza-velocità e Potenza-velocità direttamente in acqua. Questo studio pilota, potrà fornire indicazioni utili al monitoraggio e condizionamento di forza e potenza da svolgere direttamente in acqua. Infine la terza parte (capitoli 7-8), si focalizza sull’individuazione della sequenza di Fibonacci (sequenza divina) nel nuoto a stile libero e a farfalla. I risultati di questi studi suggeriscono che il ritmo di nuotata tenuto durante le medie/lunghe distanze gioca un ruolo chiave. Inoltre, il livello di autosomiglianza (self-similarity) aumenta con la tecnica del nuoto.

Genetic Aspects Of Athletic Performance: The African Runners Phenomenon.

The current dominance of African runners in long-distance running is an intriguing phenomenon that highlights the close relationship between genetics and physical performance. Many factors in the interesting interaction between genotype and phenotype (eg, high cardiorespiratory fitness, higher hemoglobin concentration, good metabolic efficiency, muscle fiber composition, enzyme profile, diet, altitude training, and psychological aspects) have been proposed in the attempt to explain the extraordinary success of these runners. Increasing evidence shows that genetics may be a determining factor in physical and athletic performance. But, could this also be true for African long-distance runners? Based on this question, this brief review proposed the role of genetic factors (mitochondrial deoxyribonucleic acid, the Y chromosome, and the angiotensin-converting enzyme and the alpha-actinin-3 genes) in the amazing athletic performance observed in African runners, especially the Kenyans and Ethiopians, despite their environmental constraints.