A novel multi-sensor hardware and software system to realistically capture 3D and 4D spatiotemporal audiovisual representations of objects, hands and hand–object interactions
Overview
From animating a character in a movie to analyzing an athlete’s performance, 4D motion capture is a technique that allows the detailed tracking and analysis of a subject’s dynamic movement in three dimensions (X,Y,Z) over time. Such technologies have widespread applications in enhancing the realism of digital characters, improving biomechanical performance of athletes and refining virtual environments, making it an invaluable tool in both scientific discovery and creative expression. Traditionally, 4D motion capture requires sophisticated arrays of cameras, sensors and lights that are synchronized via software. Yet, these systems are expensive ($200k to $2M), bulky, constrained to lab settings and can be hard to calibrate for proper synchronization between the hardware and software of the system. The disclosed technology develops a modular, inexpensive 4D motion capture system composed of multi-sensor hardware integrated with novel software algorithms to support automated 4D reconstruction. In this way, the platform is more accessible in cost and applications, allowing the fast, efficient analysis of 4D data.
Market Opportunity
The disclosed 4D motion capture technology has widespread applications in film and video game animation, sport science analysis, healthcare applications such as surgical planning, biomechanics research, product development, robotics and AI-development. In each of these fields, the present technology can provide bespoke services with 4D audiovisual capture to meet a customer’s need. Further, the data analyzed with this novel 4D capture system can be used to drive innovation. For example, generative AI systems have seen a rapid rise in the last few years, with a current market value >$40 billion. Systems like ChatGPT and StableDiffusion can generate high-quality text and images that are almost indistinguishable from those that are produced by humans. Yet, these AI systems lack “physical intelligence,” or the ability to interact with and shape environments in a human-like manner as well as datasets to be trained on. Using the novel 4D motion capture system that is disclosed, robust data can be generated to train AI models, build robots with transformative physical capabilities and deepen research of human motor cognition.
Innovation and Meaningful Advantages
The proposed technology contains a low-cost hardware system built from easily-sourced components integrated with novel software for efficient sensor calibration and synchronization as well as automated 4D reconstruction. Unlike other 4D capture systems that require extensive training due to their reliance on special hardware and proprietary control software, the disclosed technology is designed to be easily built, customized and operated by undergraduate and graduate students with basic training. Although low-cost (50X cheaper than traditional systems), the hardware technology has multiple sensors including RGB cameras, microphone array, depth sensors, LED lights and accelerometers for appropriate tracking. Because of this, the platform allows for high-fidelity capture of motion. Further, two sizes have been developed which include a table-sized system for capturing human hands, small objects and/or small robotic arms as well as a room-sized platform that can support full body capture, larger objects and robots to accommodate a wide variety of applications.
Collaboration Opportunity: We are interested in exploring research collaborations and licensing opportunities.
References
|
|
|
This technology leverages artificial intelligence (AI) and motion capture to analyze and predict human movement patterns. Using video-based tracking and sensor data, it creates a personalized digital model of an individual’s biomechanics in different movements (e.g. sitting, walking, squatting, other functional movements, etc.). This model can simulate how a person moves in different environments or under various conditions, such as fatigue or injury, to optimize performance and prevent injuries. The system is designed for applications in rehabilitation, sports, occupational safety, and military training, providing real-time insights into movement efficiency and potential risk factors.
Background:
Human movement analysis is critical in fields like physical therapy, sports training, and workplace safety, yet existing methods rely on expensive motion capture systems or subjective assessments. Current solutions often lack real-time adaptability and fail to account for individual variations in biomechanics. This technology offers a cost-effective, AI-driven alternative that provides detailed motion predictions without requiring complex or invasive equipment. By using generative AI, it can simulate movements in different scenarios, improving injury prevention and rehabilitation strategies.
Applications:
Advantages:
This invention introduces a novel method for designing optical elements, such as lenses, by using the effective medium theory (EMT). By employing subwavelength patterns in thin films or membranes, the technology creates localized refractive index changes that enable precise control over the behavior of light. This approach is particularly effective in ultraviolet (UV), deep ultraviolet (DUV), and extreme ultraviolet (EUV) wavelength ranges, offering a scalable and versatile solution for developing high-performance optical systems. Unlike traditional doping methods, this innovation achieves refractive index control through physical structuring, paving the way for advanced lenses, beam shaping, and nanomembrane applications.
Background:
Creating high-performance optical components for UV and EUV applications presents challenges, as current methods such as doping or metasurfaces often lack precision, scalability, or efficiency. Unlike doping, which also changes the effective medium index, this method relies on the physical creation of subwavelength patterns. This allows for precise tailoring of the refractive index without needing dopants or masks. Traditional approaches depend on chemical alterations that limit flexibility and require complex manufacturing processes. This technology overcomes these hurdles by leveraging EMT, using physical subwavelength patterns to manipulate light with unparalleled accuracy.
Applications:
Advantages:
This technology enables the creation of advanced optical elements through thin film coatings. By spatially varying the thickness, order, and material composition of thin film stacks, the technology allows for precise control of light's phase and amplitude. It is particularly advantageous in the extreme ultraviolet (EUV) wavelength range, where traditional optical systems struggle. This approach facilitates the design and fabrication of metasurfaces, metalenses, and other high-efficiency optical components, opening up new possibilities for EUV applications in lithography, imaging, and microscopy.
Background:
Developing optical elements for EUV applications is highly challenging due to material limitations and fabrication complexities. Current solutions, such as metasurfaces or diffractive optical elements, often suffer from low efficiency or limited phase control. This invention addresses these issues by using customizable thin film coatings that enable precise and continuous phase and amplitude control, offering a scalable and efficient alternative to traditional methods. By enabling fine control over optical properties without relying on bulky components, this method facilitates the development of next-generation optical systems for applications such as EUV lithography, microscopy, and high-resolution imaging.
Applications:
Advantages:
This technology introduces a novel method for fabricating multilayer nanophotonic devices using spin-coated planarization layers. The process ensures precise alignment and spacing between optical layers, enabling the creation of advanced optical elements for photonic computing and compound lenses. Spin coating is a procedure used to deposit uniform thin films onto flat substrates. By leveraging spin-coating techniques, the technology simplifies the integration of multiple optical layers, resulting in highly efficient and scalable solutions for nanophotonic systems.
Background:
Producing multilayer nanophotonic devices requires precise control over the spacing and alignment of optical layers, a challenge that existing fabrication methods struggle to meet. Traditional approaches often involve complex and time-consuming processes that limit scalability and consistency. This invention provides a streamlined solution, combining spin-coating technology with nanophotonic design to enhance the functionality and efficiency of optical components. The spin-coated planarization layers fill gaps and create smooth, well-aligned surfaces between layers while preserving optical properties.
Applications:
Advantages:
This technology is a quantum computing platform that uses the topological features of a classical nonlinear granular computing system to simulate quantum-like behavior using "elastic bits." These elastic bits emulate qubits by maintaining stable state integrity at ambient temperatures without the decoherence issues of quantum systems. This allows for quantum analogue computing: quantum logic and operations performed using a classical system. This quantum analogue computing method bypasses many of the challenges associated with quantum computing, such as the need for specialized, extremely low temperature environments, and the high risk of error. This method provides robust, scalable, fault-tolerant quantum analogue computing with enhanced computational density and efficiency.
Background:
Quantum computers use the properties and phenomena of quantum mechanics to operate with significantly greater speed and efficiency than classical computers. However, they can be challenging to effectively operate since any interference from their environment can cause significant error. This technology is a quantum analogue computing system that simulates quantum logic with a classical computing system, avoiding the operational challenges that make quantum computing impractical. This system offers potential for broad applications in materials-based quantum analogues, simplifying quantum computing paradigms.
Applications:
Advantages:
ãThe CO2 fixation technologies so far often use alkaline earth metals to fix CO2 by conversion into chemically stable carbonate mineral. The conventional technologies are difficult to apply on a large scale because of its slow reaction rate, high cost due to the use of a large amount of pH adjuster, and poor profitability.ã
ãThis invention discloses novel CO2 fixation enables to run under low temperatures (below 100°C) without using large amounts of pH adjusters and continuously at low cost by recycling of the input chelating agent (GLDA) during the process. This invention also enables to obtain carbonates like CaCO3 or oxides like silica with high purity by using unutilized Ca/Mg-containing wastes such as combustion ash, waste concrete, and slag as Ca/Mg sources in the CO2 fixation process. Fine chemicals like CaCO3 and silica obtained in this sustainable CO2 fixation technologies are expected to be secondary used for pigments, rubber, and desiccants.
UW-Madison researchers have developed a method to synthesize silica nanoparticles from leachates produced from mineral carbonation. High surface area silica nanoparticles are precipitated from the carbonation leachate using amino acids such as lysine. To achieve this, amino acid powders such as lysine are added to the Si-rich carbonation leachate and the solution is kept at room temperature for up to 2 hours, during which lysine instigates silica precipitation by complexing with aqueous Si species and serving as nucleation agents. Resulting silica nanoparticles can be filtered out and resuspended/redispersed in a basic solution after washing in mild acidic solution for a few minutes. During this process, the pH of the leachate is minimally affected, allowing the solution to be recycled for mineral carbonation. This is attractive compared to the traditional method of inducing silica precipitation through a pH swing (by adding mineral acid or CO2 to the solution), where the reduction of pH renders the reuse of the solution difficult. The amino acid concentration and precipitation time can be varied to control the size of the silica nanoparticles, which is also difficult to achieve using pH swing methods.