This project explored the application of computer vision technology in a social game to develop a web-based photo-bombing game for the HITLab NZ. I performed a literature research to find out more about game design and computer vision methods. Some subjects covered were the psychological background of pranks and social games. My technology research focused on varieties of computer vision to be able to recognise players in uploaded photos. Furthermore, I used the outcomes of a context mapping session with four potential users to develop an interaction vision and define requirements for a successful game. My main conclusions were that social gameplay especially was a major opportunity to include in my game, and that many different computer vision methods have different benefits and disadvantages that should be further explored before incorporating one in my design. This exploration was executed using an evolutionary design method and a design framework based on several elements of game design. Brainstorming sessions and a morphological chart led to game mechanisms that explored the idea scenarios regarding social play and the fulfilment of quests, and a technological development based on QR codes and face recognition. The final design combined both idea scenarios by offering social quests, and used face recognition as identification method. The game was developed and explained in more detail using the game design framework and various diagrams: a function diagram explaining the input, output, and processes of player, website, and servers; and a system diagram to connect the functions and interactions to form a player-friendly interface. Because of technological limitations regarding player identification found in the game development, the final user test focused on the gameplay and user experience compared to my vision and expectations. I tested the enjoyment level, balance, player retention, and tourist reactions. I found that my test persons were reluctant to cross social boundaries for more elaborate photo-bombing quests. They felt that, in theory, the game sounded like an amazing way to spend some spare time on holiday, almost like a treasure hunt. In practice, however, they hardly got round to playing it. My final recommendations were to review the choice of a broad target group and to pay a lot of attention to the implementation of the game, so it becomes socially accepted. More importantly, the success of the game depends heavily on future computer vision developments: as it stands right now, the methods I explored are not reliable enough.