Xenco Medical introduces XenVision at SIGGRAPH 2026

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Artificial intelligence is being applied across industries ranging from finance to manufacturing, and computer vision systems are increasingly being developed to analyze complex visual information. One area of development involves using cameras and software to map how the human body moves.

That was the focus of Xenco Medical’s unveiling of XenVision at SIGGRAPH 2026, an Association for Computing Machinery conference focused on computer graphics and interactive technologies. According to the company, the platform uses computer vision, biomechanics, and artificial intelligence to perform markerless movement analyses in under two minutes. The company presented XenVision as an example of how advanced computing techniques could be applied to the digital representation of human movement.

Xenco Medical says the platform applies AI-driven pose estimation to reconstruct a digital model of the body’s movement before generating data describing elements such as posture, joint positioning, range of motion, bilateral symmetry, movement efficiency, and compensatory movement patterns. The system operates through camera-based analysis rather than wearable sensors or reflective motion-capture markers.

Analyzing human movement

Traditional motion-capture systems often use physical markers or sensors to record a person’s movements. Markerless systems instead use camera footage and computer-vision models to identify body positions and translate them into digital data.

This approach can reduce the amount of specialized equipment involved in capturing movement, although the resulting analysis may be influenced by camera positioning, lighting, clothing, visibility, and the types of movement recorded. XenVision’s performance claims and descriptions are based on information supplied by Xenco Medical.

The SIGGRAPH connection

Although SIGGRAPH is best known for showcasing advances in computer graphics, simulation, and visual computing, computer vision, geometric modeling, and pose estimation have applications across fields that involve the digital representation of people and objects. Xenco Medical’s decision to introduce XenVision at the conference highlighted the overlap between these fields.

According to Haider, SIGGRAPH offered a relevant setting for the launch because the platform draws on developments in computer vision, spatial computing, and machine learning. These technologies allow software to identify points on the body, follow their positions across a sequence of images, and represent the resulting movement digitally.

Developing the platform

The performance of artificial intelligence models depends partly on the data used in their development. Systems designed to analyze human movement must account for variations in body position, camera angle, and the movement being recorded. Xenco Medical says XenVision was developed to identify movement patterns and generate standardized measurements, although the company has not disclosed detailed information about the size or composition of its development dataset.

The company describes data relevance and interpretation as important considerations in developing the platform. As with other markerless motion-analysis systems, its outputs depend on how visual inputs are captured and processed by the underlying model.

A computer-vision application

XenVision brings together artificial intelligence, computer vision, and biomechanics in a non-contact movement-analysis system. Rather than relying on equipment attached to the body, it uses visual inputs to construct a digital representation of movement and generate corresponding measurements.

Its unveiling at SIGGRAPH provides an example of how techniques developed in computer graphics and pose estimation are being used to analyze physical movement. As markerless technology develops, its accuracy and consistency across different environments and users will remain important considerations.