# PokAR: Facilitating Poker Play Through Augmented Reality

Adam Gamba<EMAIL_ADDRESS>and  Andrés Monroy-Hernández
<EMAIL_ADDRESS>Princeton UniversityPrincetonNew JerseyUSA08544

(2023)

###### Abstract.

We introduce PokAR, an augmented reality (AR) application to facilitate poker
play. PokAR aims to alleviate three difficulties of traditional poker by
leveraging AR technology: (1) need to have physical poker chips, (2) complex
rules of poker, (3) slow game pace caused by laborious tasks. Despite the
potential benefits of AR in poker, not much research has been done in the
field. In fact, PokAR is the first application to enable AR poker on a mobile
device without requiring extra costly equipment. This has been done by
creating a Snapchat Lens 111A Lens in Snapchat is an experience that utilizes
augmented reality to transform the world around you (Snap, 2022b). which can
be used on most mobile devices. We evaluated this application by instructing 4
participant dyads to use PokAR to engage in poker play and respond to survey
questions about their experience. We found that most PokAR features were
positively received, AR did not significantly improve nor hinder
socialization, PokAR slightly increased the game pace, and participants had an
overall enjoyable experience with the Lens. These findings led to three major
conclusions: (1) AR has the potential to augment and simplify traditional
table games, (2) AR should not be used to replace traditional experiences,
only augment them, (3) Future work includes additional features like increased
tactility and statistical annotations.

connected lens, augmented reality, poker, co-located, interaction,
socialization

††copyright: acmcopyright††journalyear: 2023††doi: XXXXXXX.XXXXXXX††ccs:
Human-centered computing Collaborative and social computing devices Figure 1.
Two players using the PokAR application.

##  1\. Introduction

The goal of this project is to facilitate heads-up Texas hold’em poker play
through augmented reality. Poker is cumbersome to play in its current form,
requiring players to have poker chips and knowledge of the complex rules to
play correctly. Without an experienced player to guide the game, new players
often find it difficult to learn the rules and play correctly (Sakuma et al.,
2012). Additionally, due to the burden of physical chips, it is difficult to
play poker in many scenarios (e.g., at the beach, while traveling, or
camping). Finally, the game pace is often slowed due to poker’s complex rules
and the need for laborious tasks like counting chip stacks.

Augmented reality technology is well-equipped to solve these issues in three
ways. Firstly, AR can eliminate the need for physical poker chips by instead
utilizing AR to render chips. Next, AR can help guide players through the
complex rules of poker by hinting at legal actions during gameplay. Finally,
AR can help decrease the burden of laborious tasks (like counting chips) and
increase the game pace. PokAR helps alleviate these three issues, which we’ll
discuss further throughout this paper.

Poker is a popular game, with over 120 million players worldwide playing
regularly online (Offshore, 2021). Texas hold’em is one of the most popular
poker variants. In this variant, players are dealt two private cards and five
community cards, and they battle to make the best hand or bluff opponents into
folding. ’Heads-up’ poker is a term used to describe poker played by just two
players, head-to-head. In its current state, PokAR supports only heads-up
Texas hold’em poker, but with future work, it could be extended to more
players and more variants. Throughout this paper, we will use the term ’poker’
to refer to heads-up Texas hold’em poker.

Poker is a classic example of a social, co-located game, since poker, by
design, emphasizes in-person, co-located interaction. Players often look at
each other and speak to each other during a poker game, either to gain
information or to socialize. Also, poker forces players to focus on the same
enablers, or ”physical objects that trigger and are the focus of the AR
experience” (Dagan et al., 2022). These enablers, like playing cards and poker
chips, can help guide an AR experience and engage players more closely than in
games that do not have a similar shared focus. For the above reasons, we chose
to augment poker in this study.

PokAR is not intended to replace traditional poker, rather it helps people
play when traditional poker would be difficult or impractical. The goal of AR
applications should be to disappear completely and seamlessly immerse the user
in a realistic experience that combines reality with augmentation (Weiser,
1991). This disappearance frees users to utilize these applications more
effortlessly, allowing them to focus on new goals, beyond the application
itself.

##  2\. Related Work

While we have established AR as a possible solution to the aforementioned
issues with poker, very little work has been done concerning AR poker.
Additionally, while AR is not yet a heavily explored area, researchers have
argued that “A Poker-Assistance-Software is an ideal test area for an AR
Application with real added value,” with possible areas to add value including
automation and statistical estimations (Thul, 2013).

Similar projects in the past have all relied on physical means to augment
reality. For example, researchers used overhead projectors to project all
aspects of the poker game (e.g., cards, chips, etc.) onto a table (Sakuma et
al., 2012). Additionally, researchers have used RFID playing cards to detect
the dealt cards (Sakuma et al., 2012). While this study succeeded in creating
an AR application to ease some of the same cumbersome aspects of poker tackled
by PokAR (physical chips, complex rules, slow game pace), it did so using a
high-cost solution, which is impractical for most recreational use.
Additionally, they disregarded studying how this AR setup influenced social
interactions in poker.

Furthermore, people have utilized virtual reality (VR) in the past to create
commercial poker video games. One example is PokerVR by Meta, which uses
“expressive avatars built for reading tells with growing customizations”
(Meta, 2019). While they may say this, VR poker applications still just employ
static players’ avatars, which do not emphasize the in-person, social nature
of poker.

PokAR is the first project to enable AR poker without needing additional
equipment other than a mobile device and a regular deck of cards (like an
overhead projector or a VR headset). This is a worthwhile problem because it
is the first application to enable AR poker at a low cost, since it only
requires a few commonly-owned pieces of equipment (mobile devices and playing
cards). Additionally, utilizing AR over VR allows the gameplay to emphasize
the social aspects of co-location and increase socialization when compared to
VR implementations.

Co-located gaming has been shown to lead to more effective and enjoyable
gaming, as players can more easily communicate and build social relationships
(Herodotou et al., 2015). One major reason for this is ”out-of-the-game, game-
related communication” (Herodotou, 2010). By having the ability to converse
about other topics while simultaneously being involved in a game with another
player, these players are given the opportunity to build a deeper connection.

Additionally, when comparing socialization in AR and VR, prior research tends
to support increased socialization in AR applications. AR games have the
ability to ”potentially enhance social communication and social interaction
between people” (Savela et al., 2020), whereas high-involvement in VR games
could potentially isolate users socially and ”negatively affect their well-
being” (Lee et al., 2021). Thus, we chose to develop an AR application rather
than a VR application to reap the social benefits of shared, co-located
experiences.

##  3\. PokAR System

The PokAR Snapchat Lens allows users to play heads-up poker with another
player on two mobile devices. AR visual annotations include 3D models of poker
chips which dynamically render with changing stack size, and 3D text above the
chip stacks denoting the size of each stack. 2D visual annotations include
number of hands played, current round, current dealer, previous action, amount
to call, waiting message, and UI buttons with labels ”Check,” ”Call,” ”Bet,”
”Raise,” and ”Fold.” All AR and 2D annotations render dynamically with
changing game state, stack amounts, and legal actions. PokAR implements five
main features to help achieve its motivating goals.

  * •

“3D AR Chips” - PokAR renders 3D models of chips to eliminate the requirement
of needing physical poker chips.

  * •

“UI Action Buttons” - 2D buttons rendered on the player’s screen allows them
to select among and perform legal actions at the current state of the game.

  * •

“Game Messages” - Messages provide additional information to both players
about the actions of players, bet amounts, and more throughout the game.

  * •

“Counting Stacks” - A live count of the number of chips in all chip stacks is
rendered above the 3D models, eliminating the hassle of counting chips
manually.

  * •

“Awarding Pots” - After a winner is determined (through folding or at
showdown), the chips are automatically awarded to the winner, eliminating the
hassle of moving chips manually.

###  3.1. Approach

To achieve our motivating goals, we developed a Snapchat Lens which could be
used on any mobile device to facilitate poker play through AR. Besides having
physical playing cards, players will play the game of poker in AR by
interacting with their augmented environment through a mobile device. We used
the Snap Lens Studio IDE with JavaScript for development, the Snapchat app for
testing and deployment, and GitHub for version control. Code for this project
can be found at the link in Appendix D. Physical playing cards act as an
enabler to ground the game in physical reality. A demonstration of the
completed application is shown in Fig 2. In the development of PokAR, we faced
and solved three major implementation subproblems. They will be discussed
below.

Figure 2. Side-by-side points of view of the same game of PokAR on two mobile
devices.

###  3.2. Subproblem 1: Modeling Poker in Code

The first implementation subproblem to solve was to figure out how to model a
game of poker in code. By nature of the rules of poker, the game is
deterministic based on previous player actions within a betting round. Thus,
the game state can be modeled using a Deterministic Finite Automaton (DFA).
The DFA for our application determines the legal actions and/or termination
state of the betting round, given previous actions within the betting round.
At the end of each betting round, one of two termination states is reached,
dictating whether the hand has ended or players will advance to the next
betting round. Fig 3 and Fig 4 show a graphical representation of the DFAs we
used in our implementation. In both DFAs, the application begins with the
Start state and terminates in either the endHand() or advance() state. The
double-headed arrow represents the possible cycle of betting, raising,
reraising, etc., until one of the players is eventually all-in. Player ’A’ is
the one assigned ‘opponent’ at the start of a hand, and player ’B’ is the
‘dealer.’

Figure 3. Pre-flop DFA (used before any community cards are dealt).  Figure 4.
Post-flop DFA (used once community cards have started to been dealt).

###  3.3. Subproblem 2: Rendering 3D Objects Stably

The second implementation subproblem was to figure out how to render 3D
objects in the world and effectively track them. Originally the implementation
used Snap’s World Tracking (Snap, 2022d) functionality, and then its Surface
Tracking (Snap, 2022d) functionality, with neither proving to be too accurate.
Chip stacks are small and users expect them to stay in relatively the same
position throughout a game. However, with World Tracking and Surface Tracking,
chip stacks would move throughout the room quite a bit if the mobile device’s
camera was moved.

Then, we decided to use Marker Tracking (Snap, 2022d), which uses a printed
marker pattern to mark a position in the physical world and allow the
application to render objects relative to that position. Marker tracking
proved to be very accurate and stable for rendering 3D objects in AR. Chip
stacks would no longer move throughout the room, as they were grounded in a
location in 3D space. Marker Tracking, however, is only a temporary solution
while alternative tracking solutions are improved with continued computer
vision research.

###  3.4. Subproblem 3: Connecting Multiple Players

The third implementation subproblem was to figure out how to connect two
players within a single Snapchat Lens to play together and share game data. To
solve this problem, we designed an API to connect two different mobile devices
and allow them to send messages between each other, including updates on the
game state and player actions. This API is built on top of Snap’s Connected
Lenses feature (Snap, 2022a). Thus, the two players will always observe the
same data on different devices in real time, unifying their gameplay
experience.

##  4\. Evaluation

We recruited 8 participants who were found through a poker club on campus and
recruited by email. We asked participants to respond to a pre-study survey to
learn about their individual experience with poker and its rules. This survey
can be found in Appendix B. We randomly paired participants into 4 dyads to
utilize PokAR to play heads-up poker for 25 minutes. Then, we asked them to
respond to a post-study survey about their experience with the application. In
this survey, we asked participants about the benefits and detriments of
particular PokAR features, the effects of AR on socialization, the effects of
AR on game pace, and the overall experience with PokAR. This survey can be
found in Appendix C. The study protocol above is described in more detail in
Appendix A.

##  5\. Results

Although participants had varying levels of poker expertise, they all had a
self-reported understanding of the rules. Based on the results of the pre-
study survey, we grouped the 8 participants into three groups of varying
experience levels for analysis: Highly Experienced (play poker multiple times
a week, $n=2$), Moderately Experienced (play poker weekly to monthly, $n=3$),
and Slightly Experienced (play poker yearly or less, $n=3$).

###  5.1. Evaluation of Features

We asked participants to rate each of the five major PokAR features on a scale
of 1 (detrimental) to 5 (beneficial) in terms of its effectiveness compared to
the corresponding object/action in real-life poker. Each feature earned an
average score $>3$ (leaning beneficial) among all participants. Specifically,
”3D AR Chips” scored a 4, ”UI Action Buttons” scored a 4.25, ”Game Messages”
scored a 3.875, ”Counting Stacks” scored a 4.375, and ”Awarding Pots” scored a
4.25.

Notably, the only features that scored $<3$ (leaning detrimental) were “3D AR
Chips,” “UI Action Buttons,” and “Game Messages” for the Highly Experienced
subgroup of participants. This could be explained by the fact that all three
of these features are intended to alleviate the requirement of knowing the
complex rules of poker. However, in the pre-study survey, all members of this
subgroup answered that they play poker quite often and they confidently
understand all the rules, so these features likely just got in the way of
their gameplay. The features of “Counting Stacks” and “Awarding Pots” were,
however, positively received by all three subgroups of participants.

###  5.2. Evaluation of Socialization

The average response to the survey question: “How much did AR affect the in-
person social aspects of the game of poker?” was a 3.25 on a scale of 1
(negatively) to 5 (positively), meaning that AR neither significantly improved
nor impaired the in-person social aspects of poker. This is a beneficial
result, as one of PokAR’s goals was to supplement the game of poker. We did
not implement social-related features intended to improve socialization, but
this result supports the claim that the AR features of PokAR did not impair
socialization. In other words, players are utilizing PokAR as a tool to enable
poker play, which does not get in the way of the traditional social
interactions at a poker table.

Additionally, multiple participants noted that AR did not heavily influence
socialization. P1 stated that the experience was “no different, we could still
talk and converse,” and P5 stated that AR “Didn’t affect socialization because
everything was still in person.”

###  5.3. Evaluation of Game Pace

The average response to the survey question: “How did augmented reality affect
the game pace of poker?” was a 3.75 on a scale of 1 (slowed the game) to 5
(sped up the game), meaning that AR slightly increased the game pace of poker.
In this study, the average game pace was 40.3 hands/hour (67.2 hands/hour for
the Highly Experienced subgroup). Comparatively, “A typical live poker game
will deal 25-30 per hour,” assuming 9 players (Fisk, 2020). This section
requires additional study, including a control session of each participant
group playing traditional poker to compare the game pace with AR poker.

###  5.4. Evaluation of Overall Experience

On average, participants rated their overall experience at a 4.5/5,
overwhelmingly positive. P2 stated that “It’s quicker, but annoying to hold
the phone up.” P6 stated that “It was a different experience which took a
little getting used to, but I enjoyed it.” P4 stated that it “Felt cool to
have the chips tracked for you. Definitely could see myself using it on a
camping trip or during traveling.” P5 stated that “It was cool, because
sometimes I’d like to play poker but sometimes have no chips!”

##  6\. Conclusion

Through developing a complete AR application and studying how people utilize
it, we have generated three main conclusions.

###  6.1. AR Has the Potential to Augment and Simplify Traditional Table Games

After our work throughout this semester, we are confident that AR as a
technology can and will be used in the future to augment and simplify
traditional table games, like poker. While the technology is currently in a
primitive state, it is continually evolving and progressing. Several
participants noted that the gameplay of PokAR was clunky since they had to
constantly hold their mobile devices up to see the game. However, with
improved AR technology, this annoyance will begin to fade away. For example,
AR glasses like Spectacles will eliminate the need to hold up a mobile device
(Snap, 2022c).

This study revealed promising results concerning the future potential of AR in
games. For instance, the use of AR did not hinder socialization, and
participants had a positive overall experience. PokAR features meant to
facilitate gameplay were positively received by most players, and options to
disable disruptive features would alleviate the rest.

###  6.2. AR Should Not Be Used to Replace Traditional Experiences; It Should
Be Used to Augment Them

This conclusion stems from the fact that AR technology has innate limitations
compared to the physical world. For instance, AR experiences are less tactile
than physical world experiences. While software tricks exist to improve the
tactility of AR experiences (like hand tracking, which enables object
manipulation), it will never feel quite like the physical world. For example,
several participants noted that PokAR was missing one important aspect of
traditional poker: chip shuffling. Chip shuffling is a common fidgeting
technique among poker players in which they use one hand to rearrange a stack
of chips. Shuffling is almost unanimous among poker players and is commonly
used to pass time and cure boredom during long poker sessions. While AR could
simulate chip shuffling, it could never reproduce the experience perfectly.

Early intuition about this conclusion is one reason we decided to utilize
physical playing cards in PokAR. If playing cards were virtual, players would
be playing an online poker game in which in-person social interactions were
minimal. Players wouldn’t even need to be co-located to play PokAR anymore.
This would be a case of using AR to replace a traditional game experience.
Instead, we decided to use physical cards and virtual chips in PokAR to afford
some physical-world tactility to players and streamline some of the more
annoying and time-consuming aspects of poker, like counting chips.

As mentioned in the introduction, PokAR is not intended to replace traditional
poker, only augment it. This is due to the inherent limitations of AR
technology. More broadly, AR should not be used to replace traditional
experiences, only augment them. Augmentations should be deliberately planned
and carefully implemented to ensure that they do not take over the spirit of
the game. Go too far with augmentation, and you approach the virtual reality
world and lose out on social interaction.

###  6.3. Future Work

Our work on PokAR has revealed possible directions for future study and
enhancements to the application. Firstly, due to time constraints, not all
features of poker were able to be added. PokAR is currently limited to just
two players. This design choice was made to reduce the project’s complexity,
but this limit should be increased to the accepted limit of nine players to
better simulate traditional poker. Additionally, the option to chop pots
(split pots equally between tied players) is currently not implemented. The
option to run it multiple times (deal remaining cards multiple times in an
all-in situation and award the pot proportionally to winners) is also not yet
implemented.

PokAR would benefit from increased tactility, which is why we believe that it
is a necessary direction for future work. Increased tactility could come in
two forms, with the first being the ability to grab AR chips and manipulate
them with your hands. This feature would let players bet more realistically
(rather than just clicking a button) or could help simulate chip shuffling
(which was mentioned earlier as a lacking aspect). The other way to increase
tactility would be to utilize hand gestures, rather than UI buttons, to signal
actions. For example, players could tap the table with a fist to signal a
‘check,’ as in traditional poker. These features would further increase the
immersion of PokAR.

Finally, AR could be utilized to provide helpful statistical annotations for
players. Possible annotations could include the probability of winning or the
probability of making a certain hand. To implement this feature, one must
first implement a computer vision model to recognize and classify playing
cards. This has been done in the past with high accuracy ($>99$%) (Rohlfing-
Das, 2020). This feature would further reduce the mental load on players and
help them play and learn poker more effectively.

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##  Appendix A Study Protocol

Below is the process we asked participants to follow during the study:

  1. (1)

Participants were found through a poker club on campus and recruited by email.

  2. (2)

Participants were asked to respond to the pre-study survey.

  3. (3)

The participants were randomly paired into dyads for heads-up poker play.

  4. (4)

During the study:

    1. (a)

Participants were asked to download Snapchat (if necessary) and scan a code to
gain access to the PokAR Snapchat Lens.

    2. (b)

Participants were asked to sign consent forms.

    3. (c)

Participants were asked to use PokAR to play heads-up poker (without using
real-world money) for 25 minutes.

    4. (d)

We took notes on comments, reactions, game pace, frustrations, etc. We took
photos and videos throughout. We also answered questions about the application
when asked, but we avoided guiding the players.

  5. (5)

After play, participants were asked to respond to the post-study survey.

##  Appendix B Pre-Study Survey

Below are the questions asked during the pre-study survey.

  * •

How well do you know the rules of Heads-Up Texas Hold’em Poker?

  * •

How often do you play poker?

##  Appendix C Post-Study Survey

Below are the questions asked during the post-study survey.

  * •

Please rate each of the following PokAR features in terms of its effectiveness
when compared to the corresponding object/action in real-life Texas hold’em
poker?

    * –

3D AR Chips

    * –

UI Action Buttons

    * –

Game Messages

    * –

Counting Stacks

    * –

Awarding Pots

  * •

How much did AR affect the in-person social aspects of the game of poker?

  * •

How did augmented reality affect the game pace of poker (# of hands played /
unit time)? Ignore the first few hands in which you were learning the
application.

  * •

Overall, how would you describe your experience with PokAR?

##  Appendix D Code Repository

The code for this project can be found at the following GitHub repository:
https://github.com/adamgamba/PokAR.