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By Jonan Scheffler and Aaron Patterson It all started with a dream. A dream of a world where people have learned to live in harmony with nature, where war is a distant memory, where humankind reaches unimaginable heights of technological innovation and Magic: The Gathering players no longer need to sort their cards by hand. This presentation will describe in detail the life-changing technological leaps that led us to this collectible card game utopia, examining the scanning, recognition and sorting of small bits of cardboard and all the Ruby that allows the magic to happen. If you've ever dreamed of being able to live your planeswalking dreams without the requisite hours of collating your cardboard collection, this is the presentation for you. Help us caption & translate this video! http://amara.org/v/FG1Z/
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The video titled "The Future of Computer Vision: How Two Rubyists Are Changing The World" features Jonan Scheffler and Aaron Patterson discussing advancements in computer vision through the lens of Magic: The Gathering card sorting. The speakers humorously recount their personal experiences with the card game and their shared passion for finding a way to streamline the sorting of vast collections of cards. They each devised separate solutions to tackle the problem using robotics and artificial intelligence, demonstrating their approaches and explaining their thought processes through the presentation. **Key Points Discussed:** - **Introduction of Speakers:** Jonan and Aaron introduce themselves, establishing their connection through their oversize collections of Magic: The Gathering cards. - **Problems Addressed:** Both speakers highlight the tediousness of sorting and valuing their card collections, indicating the need for technological intervention. - **High-Level Solution Overview:** The presentation outlines the overarching goals, where they aim to photograph, extract, identify, and catalog the cards automatically. - **Implementation Details:** - Jonan created a robotic solution called 'Urza' using Lego components to safely dispense cards and scan them with a camera. - Aaron developed a system using OpenCV to extract cards from images, emphasizing the challenges of camera alignment and image cropping. - **Technical Methodologies: ** - **Data Collection**: Both speakers discuss methods for gathering data and images of the cards to build a corpus for identification. - **Card Recognition**: They detail the processes they employed for recognizing cards, including perceptual hashing and Hamming distance calculations. - **Divergent Paths:** They contrast their systems, noting similarities in concept but differences in execution, strengths, and weaknesses. Jonan’s approach allows for automated scanning while Aaron’s is more manual-driven but cost-effective. - **Conclusion and Takeaways:** The presentation concludes with a call to explore future possibilities in computer vision within the context of their passion for Magic: The Gathering and encourages viewers to engage with these technological advancements in a playful manner. The humorous and personal anecdotes combined with technical details illustrate how creativity and technology can converge to solve everyday problems, particularly in niche hobbies like collectible card gaming.
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