Representation of 3D scenes is gaining popularity in industry, notably for Virtual Reality, Augmented Reality, and 360° Video. The point cloud format is well suited for such representations. Indeed, point clouds can be created with a simple capture process and modest processing, enabling a real-time, end-to-end point cloud distribution chain. However, point clouds can consume significant bandwidth -- a person modeled with point clouds can require the same bandwidth as uncompressed HD video, i.e., several gigabits per second -- so point cloud compression is required to obtain data rates and files sizes that could be economically viable by the industry. Standardization is required to ensure interoperability. In 2020, the Moving Picture Experts Group (MPEG) will publish a standard for its first point cloud codec, MPEG-I part 5: 3VC (Visual Volumetric Video-based Coding) and V-PCC (Video-based Point Cloud Compression). This standard enables a world of new services and applications, including cultural heritage, telepresence, and new forms of entertainment. An initial V-PCC codec architecture was submitted in response to the call for proposals in October 2017. This architecture was enriched by tools improving coding performance or minimizing 3D object reconstruction artifacts, thereby improving visual quality. First, we review the principal use cases targeted by the V-PCC standard, present the architecture of the V-PCC codec, and describe tools adopted within. Second, we present the methodology established for evaluation of the V-PCC codec performance and the methodology’s origins as a collaboration between industry and academics. This methodology was applied to the MPEG point cloud compression test model software (named TMC2) to consistently evaluate technologies proposed during the standardization process. Third, we compare the performance of the main V-PCC tools used for applications permitting lossy compression. This analysis is organized by tool sets that correspond to profiles, where each profile is characterized by comparable information on visual quality at a given bitrate. Further, the complexity of the main tools is analyzed from both the encoder and decoder perspective. Example pictures illustrate the impact of tool selection and bitrate. In a conclusion section, recommendations on profile usage are given according to use cases in order to support deployments of V-PCC.