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Argus Rosenhaim
R&D Engineer @ Omniflow | Master's in Computer Vision, Electrical Engineer
With more than a decade of experience in video engineering and technology, Argus Rosenhaim is a skilled Electrical Engineer with a strong focus on delivering top-notch solutions for the broadcast, media, and entertainment sectors.
Having recently completed a Master's Degree in Computer Vision from Universidade do Porto, Argus has honed his expertise in areas like artificial intelligence, machine learning, and cloud computing.
Currently an integral part of the professional services team at GLOOKAST, a prominent provider of media workflow solutions, Argus is involved in designing, installing, configuring, and supporting intricate video systems and workflows for clients globally.
Collaborating closely with sales, engineering, and product departments, Argus ensures that client needs are fully met through customized solutions that align with their expectations.
In his role, besides offering technical training, documentation, and troubleshooting assistance to clients, Argus also focuses on maintaining efficient system operations. His daily tasks involve leveraging skills in single-board computers, live video streaming, and programming.
Argus Rosenhaim's educational background includes a Master's degree in Computer Science from Universidade do Porto, a Bachelor of Engineering (B.Eng.) in Electrical Engineering from Federal University of Rio Grande do Sul, and studies in Industrial Electronics Technology/Technician at Fundação Liberato.
His professional journey features roles such as AI Engineer at Omniflow, System Engineer Professional Services at GLOOKAST, Support Engineer at CIS Group Corp, Broadcast Services at CIS Group Corp, Support Analyst at Grupo RBS, Video Engineer at Zeppelin Films, Owner at AV Tecnologias Inovadoras, and Manutenção e TI at KROMAK FOTOGRAFIA E PUBLICIDADE.
Highlights
Exciting updates from the timelapse camera project! 📷
Innovative features have been introduced to streamline installation and capture diverse perspectives. Navigating construction sites, with their resource and machinery constraints, demands precise planning. Since installing cameras isn't the usual task for construction workers, the goal is to make it seamless and efficient.
Construction environments are dynamic, with activities and resources shifting constantly. To address this, a remote adjustment system has been developed. Now, using DC motors with a reduction gearbox and 3D-printed nylon parts, the tilt angle and focus of the camera can be easily modified. This ensures adaptability to changing site dynamics without disrupting the construction flow.
Stay tuned for more updates on this project as it continues to enhance its capabilities! 🔧🏗️ #Innovation #ConstructionTech #TimelapseCamera #ProjectUpdates #RaspberryPi #PiCameraHQ
Unlocking the Potential of Computer Vision: From Pixels to Progress
In the era of digital innovation, computers have been our trusted companions in the world of image manipulation. Skilled professionals have used them for corrections, alterations, video editing, and more. But did you know that since the 1960s, researchers began harnessing its power to process and analyze visual data? By the 1970s, pattern recognition became a reality. Over the decades, algorithms grew more sophisticated, and found their niche in various specialized applications, such as industrial inspection and sorting.
Around a decade ago, machine learning made its grand entrance into this field, gradually superseding other approaches and expanding the horizon of possibilities. While classical methods are still relevant, most cutting-edge applications of Computer Vision today owe their success to Artificial Intelligence.
So, what exactly is Computer Vision?
In essence, it's the art of extracting meaningful information from digital images and, at times, taking action or offering recommendations based on this data. Some of the fascinating applications include:
- Self-driving cars
- Facial recognition
- Traffic analysis
- Medical imaging diagnostics
- Agricultural monitoring
- Aerospace guidance
During my master's degree at Faculdade de Engenharia da Universidade do Porto, I embarked on a journey to choose a thesis topic. I attended classes covering a range of applications, but my engineering mindset urged me to find a problem worth solving. Surprisingly, despite the vast potential of Computer Vision in the biomedical field, it didn't immediately catch my attention.
Returning to my engineering perspective, I realized that there's more than one way to approach problems. Instead of fixing issues after they occur, why not work on preventing them in the first place? Often, prevention is not only more effective but also more cost-efficient.
From this perspective, the idea of applying Computer Vision to evaluate sports activities emerged. Imagine having a virtual coach that meticulously examines every detail of your movements, offering feedback for self-improvement and aiding in injury prevention. This concept is particularly valuable for exercises with multiple repetitions and a high degree of freedom, like gymnastics and weightlifting. These activities attract millions of CrossFit enthusiasts worldwide, many of whom lack a background in these disciplines.
My thesis successfully demonstrated the suitability of this technology for such applications. As a result, we can anticipate the emergence of AI-powered solutions in gyms in the near future.
The world of Computer Vision is constantly evolving, and its impact on diverse fields is undeniable. I'm excited to be a part of this journey and to witness the transformative potential it holds for the world of sports and beyond. 🚀💪 #ComputerVision #AI #SportsTech #Innovation Universidade do Porto
