1. Liga Predictions

Understanding the tactical approaches of each team can provide deeper insights into how tomorrow's matches might unfold. Here are some strategic elements to consider:

HC Košice vs. HK Poprad

HC Košice: Expected to leverage their home advantage by maintaining aggressive forechecking and capitalizing on power-play opportunities.
HK Poprad: Likely to focus on disciplined defensive play and quick transitions to counter-attack whenever possible.

This matchup will test both teams' adaptability as they navigate each other’s strengths and weaknesses throughout the game.

<|repo_name|>gopinathstha/USC-School-of-Cinema-Thesis<|file_sep|>/Chapter_4/chapter4.tex chapter{Preliminary Study} label{chapter:preliminary_study} The previous chapters discussed my proposed system for creating interactive environments using stereoscopic camera-based systems using standard video capture hardware. In this chapter I will present my preliminary study which was conducted as part of my initial exploration into interactive environments using stereoscopic camera-based systems. The first section presents my methodology which outlines how I created an interactive environment using a standard webcam as well as what software I used for interaction. The second section presents my results which includes what I was able to achieve using this system as well as its limitations. The third section presents my analysis of these results. section{Methodology} label{sec:methodology} For my preliminary study I used standard webcams placed at either end of a room facing each other at eye level as stereoscopic cameras. These webcams were then connected via USB ports directly onto a desktop computer which was running textit{Unity} cite{unity} with textit{Cinemachine} cite{cinemachine} installed. I used textit{Kinect SDK} cite{kinektSDK} along with textit{Kinect Fusion} cite{kinektFusion} footnote{textit{Kinect Fusion} is a module within textit{Kinect SDK}.} libraries which allow me to use depth data from Kinect v2 devices. I used two Kinect v2 devices which were placed on either side of the room where they were able capture users within its field of view. begin{figure}[!ht] centering includegraphics[width=0.8linewidth]{figures/chapter4/kinect_diagram} caption{Diagram showing how Kinect v2 devices were placed in relation to each other and also in relation to stereoscopic cameras} label{fig:kinect_diagram} end{figure} As shown in Figure~ref{fig:kinect_diagram}, Kinect v2 devices were placed on either side of the room facing towards each other with stereoscopic cameras located directly above them. Both Kinect v2 devices were calibrated using its built-in calibration function so that they would accurately measure depth data from users within its field of view. I also manually aligned these Kinect v2 devices so that they would point towards each other in order that they would be able see each other. This was done by making sure that both Kinect v2 devices had an equal distance between themselves while pointing towards each other at approximately eye level as shown in Figure~ref{fig:kinect_diagram}. I then used these two Kinect v2 devices along with its built-in depth data function so that I could create a single volumetric mesh model of users within its field of view. This mesh model was then fed into Unity using custom scripts written in C# language so that it would be able track users within its field of view within Unity. I used this volumetric mesh model along with Unity’s physics engine so that I could create collisions between users within Unity’s environment along with its own virtual objects such as walls or obstacles. This allowed me to create interactive environments where users could physically interact with virtual objects such as walls or obstacles using collision detection functions provided by Unity’s physics engine along with volumetric mesh models generated by Kinect v2 devices’ depth data function. Finally I tested this setup using two users who stood in front of these stereoscopic cameras while wearing VR headsets connected directly onto another computer running Oculus Rift software development kit (SDK) cite{oRiftSDK} which allowed me view these interactive environments through virtual reality headsets. This allowed me test whether or not it was possible for users wearing VR headsets see themselves within these interactive environments using stereoscopic camera-based systems. section{Results} label{sec:results} The following sections describe what I was able achieve using this setup along with its limitations which I discovered during testing phase. Firstly I was able create volumetric mesh models from two Kinect v2 devices’ depth data function which allowed me track users within its field of view within Unity’s environment while also allowing me create collisions between them along with virtual objects such as walls or obstacles using collision detection functions provided by Unity’s physics engine along with volumetric mesh models generated by Kinect v2 devices’ depth data function. Secondly I was able test whether or not it was possible for users wearing VR headsets see themselves within these interactive environments using stereoscopic camera-based systems by connecting Oculus Rift headsets directly onto another computer running Oculus Rift SDK which allowed me view these interactive environments through virtual reality headsets while also being able track myself moving around within them using Oculus Rift headset’s built-in tracking function along with volumetric mesh models generated by Kinect v2 devices’ depth data function while also being able interact physically with virtual objects such as walls or obstacles using collision detection functions provided by Unity’s physics engine along with volumetric mesh models generated by Kinect v2 devices’ depth data function However there were several limitations that I discovered during testing phase which include: Firstly there was significant latency when trying view myself moving around within these interactive environments through virtual reality headsets because volumetric mesh models generated by Kinect v2 devices’ depth data function had significant latency when trying update themselves every frame due mainly because there was significant delay when trying transfer data from Kinect v2 devices onto another computer running Oculus Rift SDK which caused volumetric mesh models generated by Kinect v2 devices’ depth data function had significant latency when trying update themselves every frame causing significant latency when trying view myself moving around within these interactive environments through virtual reality headsets Secondly there was significant lag when trying interact physically with virtual objects such as walls or obstacles using collision detection functions provided by Unity’s physics engine along with volumetric mesh models generated by Kinect v2 devices’ depth data function because volumetric mesh models generated by Kinect v2 devices’ depth data function had significant latency when trying update themselves every frame due mainly because there was significant delay when trying transfer data from Kinect v2 devices onto another computer running Oculus Rift SDK which caused volumetric mesh models generated by Kinect v2 devices’ depth data function had significant latency when trying update themselves every frame causing significant lag when trying interact physically with virtual objects such as walls or obstacles using collision detection functions provided by Unity’s physics engine along with volumetric mesh models generated by Kinect v2 devices’ depth data function Thirdly there was limited tracking accuracy when trying track myself moving around within these interactive environments through virtual reality headsets because volumetric mesh models generated by Kinect v2 devices’ depth data function had limited tracking accuracy due mainly because there was limited resolution available from two standard webcams placed at either end of room facing each other at eye level while also having limited field of view available from two standard webcams placed at either end of room facing each other at eye level which caused volumetric mesh models generated by Kinect v2 devices’ depth data function had limited tracking accuracy when trying track myself moving around within these interactive environments through virtual reality headsets Finally there were several issues related specifically towards usability such as difficulty adjusting focus properly due mainly because stereoscopic cameras were placed directly above user while also having difficulty adjusting brightness levels properly due mainly because lighting conditions varied greatly throughout room causing difficulty adjusting brightness levels properly section{Analysis} label{sec:analysis} The results presented above indicate that it is indeed possible create interactive environments where users can physically interact virtually objects such as walls or obstacles using stereoscopic camera-based systems however there are several limitations that need addressed before such systems become practical applications including significant latency issues related specifically towards updating volumetric mesh models generated from two standard webcams placed at either end room facing each other at eye level while also having limited tracking accuracy related specifically towards tracking users moving around within interactive environments created specifically towards stereoscopic camera-based systems due mainly because stereoscopic cameras are limited resolution available while also having limited field available specifically towards stereoscopic cameras placed directly above user while also having difficulty adjusting focus properly due mainly because lighting conditions varied greatly throughout room causing difficulty adjusting focus properly These limitations suggest that further research needs conducted specifically towards improving performance specifically towards updating volumetric mesh models generated from two standard webcams placed at either end room facing each other at eye level while also improving tracking accuracy specifically towards tracking users moving around within interactive environments created specifically towards stereoscopic camera-based systems while also improving usability specifically towards adjusting focus properly specifically towards stereoscopic cameras placed directly above user while also improving usability specifically towards adjusting brightness levels properly specifically towards stereoscopic cameras placed directly above user Furthermore further research needs conducted specifically towards exploring alternative methods specifically towards creating interactive environments where users can physically interact virtually objects such as walls or obstacles without relying solely upon stereoscopic camera-based systems including exploring alternative methods specifically towards capturing depth information specifically towards creating volumetric mesh models without relying solely upon standard webcams placed at either end room facing each other at eye level including exploring alternative methods specifically towards tracking users moving around within interactive environments created specifically towards stereoscopic camera-based systems without relying solely upon standard webcams placed directly above user including exploring alternative methods specifically towards adjusting focus properly without relying solely upon lighting conditions varied greatly throughout room including exploring alternative methods specifically towards adjusting brightness levels properly without relying solely upon lighting conditions varied greatly throughout room In conclusion although preliminary study presented above indicates that it is indeed possible create interactive environments where users can physically interact virtually objects such as walls or obstacles using stereoscopic camera-based systems however further research needs conducted specifically towards addressing several limitations identified during testing phase including addressing significant latency issues related specifically towards updating volumetric mesh models generated from two standard webcams placed at either end room facing each other at eye level while also addressing limited tracking accuracy related specifically towards tracking users moving around within interactive environments created specifically towards stereoscopic camera-based systems while also addressing usability issues related specifically towards adjusting focus properly due mainly because stereoscopic cameras are placed directly above user while also addressing usability issues related specifically towards adjusting brightness levels properly due mainly because lighting conditions varied greatly throughout room Furthermore further research needs conducted specifically towards exploring alternative methods specifically towards creating interactive environments where users can physically interact virtually objects such as walls or obstacles without relying solely upon stereoscopic camera-based systems including exploring alternative methods specifically towards capturing depth information specifically towards creating volumetric mesh models without relying solely upon standard webcams placed at either end room facing each other at eye level including exploring alternative methods specifically towards tracking users moving around within interactive environments created specifically towards stereoscopic camera-based systems without relying solely upon standard webcams placed directly above user including exploring alternative methods specifically towards adjusting focus properly without relying solely upon lighting conditions varied greatly throughout room including exploring alternative methods specifically towards adjusting brightness levels properly without relying solely upon lighting conditions varied greatly throughout room <|file_sep|>chapter{Related Work} In this chapter I will review some existing research on Interactive Virtual Reality

1. Liga stats & predictions

Slovakia

1. Liga

Overview of Ice-Hockey 1. Liga Slovakia Matches

Scheduled Matches and Teams

Expert Betting Predictions

Detailed Match Analysis

HC Košice vs. HK Poprad

MŠK Žilina vs. HK Spišská Nová Ves

HKm Zvolen vs. MHk 32 Liptovský Mikuláš

Key Player Performances

Tactical Insights

HC Košice vs. HK Poprad