Prophesee has launched an evaluation kit for developers of computer vision systems looking to evaluate Sony’s new IMX636ES HD stacked event-based vision sensor. The sensor itself was developed in collaboration between Sony and Prophesee, providing stacked event-based vision sensing that detects only subject changes.
The evaluation kit provides computer vision engineers with a tested solution for efficient technology onboarding and rapid application prototyping and development. The kit is natively compatible with free software from Prophesee and includes premium-level technical support.
Machine learning algorithms have opened up a realm of possibilities to enable vision embedded in products that make our home, workspaces and the places in between safer and more efficient. To truly realize the potential of smart vision in more use cases, developers need more power-efficient, and more flexible embedded solutions that can operate on batteries, be easy to install and maintain, and still deliver the vision performance required to provide effective and intelligent sensing of the things we want to detect and monitor. New advances in ML modeling and processing hold the key to widespread adoption of smart cameras.
Most executives we talk to about internet of things (IoT) security emphasize similar points: the need for a strong root of trust, proper authentication mechanisms, and resilience. However, there are many different ways of enabling the various aspects of this security. One company focused on physical unclonable function (PUF) based security intellectual property is Intrinsic ID.
We caught up with CEO and a founder of Intrinsic ID, Pim Tuyls, to understand more about the world of PUF security, the challenges for IoT security as technology scales, and how to deal with the potential impact of other threats including quantum computing.
Pim Tuyls co-founded the company in 2008 as a spinout from Philips Research. While working as a principal scientist managing the cryptography cluster at Philips, he initiated the original work on physical PUFs that forms the basis of the Intrinsic ID core technology. As a result of over 20 years working on semiconductors and security, Pim is widely recognized for his work in the field of SRAM PUFs and security for embedded applications.
This article covers the basics of what an SRAM PUF (physical unclonable function) is and how it works, as well as the functionality it offers in internet of things (IoT) security as the trust anchor for any device.
In any given situation, security starts with trust. When you have an alarm system in your house, you give out its pin code only to people you trust. Whether it is a family member or your friendly neighbor, without trust you do not share your secret. And that is how it is supposed to be!
This matter of trust also translates to personal identification. Here the foundation of trust comes from formal documents, such as a passport or a birth certificate. However, these documents need to be “securely linked” to a specific person. This typically works with human biometrics. ID papers all have something that ties the document to the right person, whether it is merely a picture of the person or biometric identification through fingerprints, as in modern passports. So, the biometrics are the security anchor on which a system with permissions (do you get to cross the border?) is built.
This security anchor is necessary to prevent a simple document from being copied and used by unauthorized parties. If the document is anchored to something that cannot be copied or cloned, like fingerprints, the security becomes strong enough to turn a relatively simple document into a powerful authentication tool.
Researchers at the National University of Singapore recently demonstrated the advantages of using neuromorphic sensor fusion to help robots grip and identify objects.
It’s just one of a number of interesting projects they’ve been working on including developing a new protocol for transmitting tactile data, building a neuromorphic tactile fingertip, and developing new visual-tactile datasets for the development of better learning systems.
Event-based vision is a growing field of research, and applications are starting to emerge. To accelerate the pace of innovation in machine vision systems, Paris-based Prophesee has launched its Metavision Intelligence Suite, a software toolkit that provides algorithms, code samples, and ready-to-use applications.
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