JPEG Pleno will integrate various modalities of plenoptic content under a single framework in a seamless manner. Efficient and powerful point cloud representation is a key feature of this vision. In this context a point cloud refers to data representing positions of points in space, expressed in a given three-dimensional coordinate system, the so-called geometry. This geometrical data can be accompanied with per-point attributes of varying nature (e.g. color or reflectance). Such datasets are usually acquired with a 3D scanner, LIDAR or created using 3D design software and can subsequently be used to represent and render 3D surfaces. Combined with other types of data (like light field data), point clouds open a wide range of new opportunities, notably for immersive browsing and virtual reality applications.

Learning-based solutions are the state of the art for several computer vision tasks, such as those requiring high-level understanding of image semantics, e.g., image classification, face recognition and object segmentation, but also 3D processing tasks, e.g. visual enhancement and super-resolution. Recently, learning- based point cloud coding solutions have shown great promise to achieve competitive compression efficiency compared to available conventional point cloud coding solutions at equivalent subjective quality. Building on a history of successful and widely adopted coding standards, JPEG is well positioned to develop a standard for a learning-based point cloud coding.

During the 94th JPEG meeting, the JPEG Committee released a Final Call for Proposals on JPEG Pleno Point Cloud Coding. This call addresses learning-based coding technologies for point cloud content and associated attributes with emphasis on both human visualization and decompressed/reconstructed domain 3D processing and computer vision with competitive compression efficiency compared to point cloud coding standards in common use, with the goal of supporting a royalty-free baseline. This Call was released in conjunction with new releases of the JPEG Pleno Point Cloud Use Cases and Requirements and the JPEG Pleno Point Cloud Common Training and Test Conditions. Interested parties are invited to register for this Call by the deadline of the 31st of March 2022.

To stay informed on JPEG Pleno Point Cloud activities, please regularly consult the jpeg.org website and/or subscribe to the e-mail reflector.