title: Context-aware framework for analysis of horse-race videos

authors: Hedayati, Mohammad

subjects: sports analysis systems

abstract: Today sports analysis systems draw the attention of many commercial entities and are providing many opportunities for computer vision researchers to study and develop automated sports analysis systems. The primary objective of a sports video analysis is to interpret low-level visual features to high-level semantics that can be understood by the end user. Although all sports video analysis systems are based on similar principles at the low-level visual extraction, interpreting this visual information to high-level human understanding is extremely specific to the sport in question.
This project is the very first attempt to evaluate the jockeys’ performance from horse-race TV broadcasts. The aim of this thesis is to extract high-level information from the horse race by automatically detecting and tracking jockeys, specifically at turning points of the race. However, detecting and tracking of jockeys are extremely difficult. This is because in most horse-races there are more than six jockeys and they closely follow each other to gain a leading position,
consequently locating jockeys and maintaining their identities through a video sequence is highly challenging due to the frequent occlusion. In addition, the background in horse-race videos is continually changing, thus there is not only background clutter but the jockeys themselves may be obscured by obstacles such as trees, towers and bars.
To tackle these challenges, a context-aware analysis system is proposed. The proposed system is developed based on deterministic reasoning which was obtained by observing various horse races. One important property of horse-races is the group dynamic behaviour of jockeys in the race. The jockeys race around
a circular track and the camera typically follow the jockeys, thus the jockeys relative to each other tend to move as a slowly changing group. This homogeneous characteristic of jockeys in the race is very useful, especially when local information of jockeys is poor or abrupt due to occlusion or background clutter.
The proposed system combines multiple cues, such as local jockeys’ information, background characteristics and group dynamic properties, to detect and track jockeys around a turning segment of a horse-race. We demonstrate that our proposed system can be generalized to work on other domains. The outline of the proposed model contains three modules; (1) scene analysis (2) jockey detection and, (3) tracking and data association. The main objective of scene
analysis is to extract the turning segment in the race. The detection of jockeys is accomplished by determining the location of each jockey’s cap. For the tracking of the jockeys, we implement a robust hierarchical tracking scheme which iteratively adapts and updates itself by gathering the jockeys’ properties at each of the point, object and group levels. To boost the tracking accuracy, data association is applied as a multi-target management system to maintain multiple jockeys’
identities over time, to initialise the tracking and to terminate trajectories.

text: Context-aware framework for analysis of horse-race videos Today sports analysis systems draw the attention of many commercial entities and are providing many opportunities for computer vision researchers to study and develop automated sports analysis systems. The primary objective of a sports video analysis is to interpret low-level visual features to high-level semantics that can be understood by the end user. Although all sports video analysis systems are based on similar principles at the low-level visual extraction, interpreting this visual information to high-level human understanding is extremely specific to the sport in question.
This project is the very first attempt to evaluate the jockeys’ performance from horse-race TV broadcasts. The aim of this thesis is to extract high-level information from the horse race by automatically detecting and tracking jockeys, specifically at turning points of the race. However, detecting and tracking of jockeys are extremely difficult. This is because in most horse-races there are more than six jockeys and they closely follow each other to gain a leading position,
consequently locating jockeys and maintaining their identities through a video sequence is highly challenging due to the frequent occlusion. In addition, the background in horse-race videos is continually changing, thus there is not only background clutter but the jockeys themselves may be obscured by obstacles such as trees, towers and bars.
To tackle these challenges, a context-aware analysis system is proposed. The proposed system is developed based on deterministic reasoning which was obtained by observing various horse races. One important property of horse-races is the group dynamic behaviour of jockeys in the race. The jockeys race around
a circular track and the camera typically follow the jockeys, thus the jockeys relative to each other tend to move as a slowly changing group. This homogeneous characteristic of jockeys in the race is very useful, especially when local information of jockeys is poor or abrupt due to occlusion or background clutter.
The proposed system combines multiple cues, such as local jockeys’ information, background characteristics and group dynamic properties, to detect and track jockeys around a turning segment of a horse-race. We demonstrate that our proposed system can be generalized to work on other domains. The outline of the proposed model contains three modules; (1) scene analysis (2) jockey detection and, (3) tracking and data association. The main objective of scene
analysis is to extract the turning segment in the race. The detection of jockeys is accomplished by determining the location of each jockey’s cap. For the tracking of the jockeys, we implement a robust hierarchical tracking scheme which iteratively adapts and updates itself by gathering the jockeys’ properties at each of the point, object and group levels. To boost the tracking accuracy, data association is applied as a multi-target management system to maintain multiple jockeys’
identities over time, to initialise the tracking and to terminate trajectories.

year: 2018

title: Statistical downscaling of regional daily precipitation over southeast Australia based on self-organizing maps

authors: Yin, Chonghua

subjects: self-organizing maps

abstract: This paper presents a novel statistical downscaling method based on a non-linear classification technique known as self-organizing maps (SOMs) and has therefore been named SOM-SD. The relationship between large-scale atmospheric circulation and local-scale surface variable was constructed in a relatively simple and transparent manner. For a specific atmospheric state, an ensemble of possible values was generated for the predictand following the Monte Carlo method. Such a stochastic simulation is essential to explore the uncertainties of climate change in the future through a series of random re-sampling experiments. The novel downscaling method was evaluated by downscaling daily precipitation over Southeast Australia. The large-scale predictors were extracted from the daily NCAR/NCEP reanalysis data, while the predictand was high-resolution gridded daily observed precipitation (1958–2008) from the Australian Bureau of Meteorology. The results showed that the method works reasonably well across a variety of climatic zones in the study area. Overall, there was no particular zone that stands out as a climatic entity where the downscaling skill in reproducing all statistical indices was consistently lower or higher across seasons than the other zones. The method displayed a high skill in reproducing not only the climatologic statistical properties of the observed precipitation, but also the characteristics of the extreme precipitation events. Furthermore, the model was able to reproduce, to a certain extent, the inter-annual variability of precipitation characteristics.

text: Statistical downscaling of regional daily precipitation over southeast Australia based on self-organizing maps This paper presents a novel statistical downscaling method based on a non-linear classification technique known as self-organizing maps (SOMs) and has therefore been named SOM-SD. The relationship between large-scale atmospheric circulation and local-scale surface variable was constructed in a relatively simple and transparent manner. For a specific atmospheric state, an ensemble of possible values was generated for the predictand following the Monte Carlo method. Such a stochastic simulation is essential to explore the uncertainties of climate change in the future through a series of random re-sampling experiments. The novel downscaling method was evaluated by downscaling daily precipitation over Southeast Australia. The large-scale predictors were extracted from the daily NCAR/NCEP reanalysis data, while the predictand was high-resolution gridded daily observed precipitation (1958–2008) from the Australian Bureau of Meteorology. The results showed that the method works reasonably well across a variety of climatic zones in the study area. Overall, there was no particular zone that stands out as a climatic entity where the downscaling skill in reproducing all statistical indices was consistently lower or higher across seasons than the other zones. The method displayed a high skill in reproducing not only the climatologic statistical properties of the observed precipitation, but also the characteristics of the extreme precipitation events. Furthermore, the model was able to reproduce, to a certain extent, the inter-annual variability of precipitation characteristics.

year: 2010

title: Repositioning within indigenous discourses of transformation and self-determination

authors: Berryman, Mere

subjects: research-whanau

abstract: This thesis reflectively and critically examines a series of research case studies initiated by a research-whānau. It explores the thinking, experiences and reflections of this research-whānau, as they worked to enhance the educational achievement of Māori students. Authorship of the thesis was undertaken by me (Mere Berryman). However, the methodology involved a collaborative, retrospective and critical reflection of research-whānau experiences and thinking, in the light of the research findings and experiences since the inception of this research-whānau in 1991. In the course of this work, the research-whānau have been able to explore what it has meant to put the principles of kaupapa Māori research into practice while working within a mainstream organisation (Specialist Education Services then the Ministry of Education). Our research work has involved repositioning ourselves from dependence on Western research methodologies to a better understanding and application of kaupapa Māori conceptualisations of research. 
The thesis begins by identifying mainstream and kaupapa Māori events that have historically and still continue to impact upon Māori students' educational experiences. These events provide the wider context for the work of this research-whānau at the interface of Te Ao Māori and Te Ao Pākehā, and for the 11 case studies that exemplify changes in our thinking and research practice over a period of 15 years. The thesis employs an indigenous (and specifically Māori) worldview as the framework for description, critical reflection, and theorising around these case studies. Common themes are collaboratively co-constructed then each theme is explained in relation to relevant Māori theory.
The thesis concludes with the shifts in theorising and practice made by the research-whānau during the course of our work as we sought to contribute in ways that were more transformative and self-determining. We argue that these shifts in theorising and practice are also required of others if we are to change the status quo and contribute constructively to improving Māori students' potential.

text: Repositioning within indigenous discourses of transformation and self-determination This thesis reflectively and critically examines a series of research case studies initiated by a research-whānau. It explores the thinking, experiences and reflections of this research-whānau, as they worked to enhance the educational achievement of Māori students. Authorship of the thesis was undertaken by me (Mere Berryman). However, the methodology involved a collaborative, retrospective and critical reflection of research-whānau experiences and thinking, in the light of the research findings and experiences since the inception of this research-whānau in 1991. In the course of this work, the research-whānau have been able to explore what it has meant to put the principles of kaupapa Māori research into practice while working within a mainstream organisation (Specialist Education Services then the Ministry of Education). Our research work has involved repositioning ourselves from dependence on Western research methodologies to a better understanding and application of kaupapa Māori conceptualisations of research. 
The thesis begins by identifying mainstream and kaupapa Māori events that have historically and still continue to impact upon Māori students' educational experiences. These events provide the wider context for the work of this research-whānau at the interface of Te Ao Māori and Te Ao Pākehā, and for the 11 case studies that exemplify changes in our thinking and research practice over a period of 15 years. The thesis employs an indigenous (and specifically Māori) worldview as the framework for description, critical reflection, and theorising around these case studies. Common themes are collaboratively co-constructed then each theme is explained in relation to relevant Māori theory.
The thesis concludes with the shifts in theorising and practice made by the research-whānau during the course of our work as we sought to contribute in ways that were more transformative and self-determining. We argue that these shifts in theorising and practice are also required of others if we are to change the status quo and contribute constructively to improving Māori students' potential.

year: 2008