https://patents.google.com/patent/US20200273180A1/enDeformable...

https://patents.google.com/patent/US20200273180A1/en

Deformable object tracking

if you read through the WIPO report on patentability of the Apple patent for object tracking, the very first item referenced by the WIPO report is this research:

https://ieeexplore.ieee.org/abstract/document/7063246

An Asynchronous Neuromorphic Event-Driven Visual Part-Based Shape Tracking

Abstract:
Object tracking is an important step in many artificial vision tasks. The current state-of-the-art implementations remain too computationally demanding for the problem to be solved in real time with high dynamics. This paper presents a novel real-time method for visual part-based tracking of complex objects from the output of an asynchronous event-based camera. This paper extends the pictorial structures model introduced by Fischler and Elschlager 40 years ago and introduces a new formulation of the problem, allowing the dynamic processing of visual input in real time at high temporal resolution using a conventional PC. It relies on the concept of representing an object as a set of basic elements linked by springs. These basic elements consist of simple trackers capable of successfully tracking a target with an ellipse-like shape at several kilohertz on a conventional computer. For each incoming event, the method updates the elastic connections established between the trackers and guarantees a desired geometric structure corresponding to the tracked object in real time. This introduces a high temporal elasticity to adapt to projective deformations of the tracked object in the focal plane. The elastic energy of this virtual mechanical system provides a quality criterion for tracking and can be used to determine whether the measured deformations are caused by the perspective projection of the perceived object or by occlusions. Experiments on real-world data show the robustness of the method in the context of dynamic face tracking.


One of the co-authors is Ryad Benosman


featured in the article:

https://www.eetimes.eu/a-shift-in-computer-vision-is-coming/

Enter neuromorphic vision. The basic idea is inspired by the way biological systems work, detecting changes in the scene dynamics rather than analyzing the entire scene continuously. In our castle analogy, this would mean having guards keep quiet until they see something of interest, then shout their location to sound the alarm. In the electronic version, this means having individual pixels determine whether they see something relevant.

“Pixels can decide on their own what information they should send,” said Benosman.“Instead of acquiring systematic information, they can look for meaningful information — features. That’s what makes the difference.”---

Ryad Benosman being a co-founder of Prophesee

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if you look at all the other items referenced you get an idea of what type of innovations are involved in the patent:


its very neuromorphic.