Point Cloud Compression in India: A Deep Patent Base, Thin Startup Activity

What it is

Point cloud compression (PCC) shrinks the massive data files generated by 3D sensors—sets of points in space with attributes like colour and reflectance—so they can be stored and streamed efficiently. Without compression, a single LiDAR scan can run to gigabytes, making real-time applications impractical.

MPEG has standardised two codecs: Geometry-based PCC (G-PCC) compresses 3D structures directly using octrees, while Video-based PCC (V-PCC) projects the cloud onto 2D planes and encodes them with existing video codecs. A third wave of AI-driven learned compression is now emerging, promising better rate-distortion performance.

The technology underpins autonomous vehicles, AR/VR, 3D mapping, robotics, and digital twins. As these fields scale, efficient point cloud handling becomes a hard requirement, not a nice-to-have.

The value chain

The value chain spans hardware capture to end-user rendering. Defensible IP and margin concentrate in the compression algorithms and the rendering/application layers, where performance differentiation directly impacts user experience.

• 3D Data Capture: LiDAR, depth cameras, photogrammetry.
• Point Cloud Generation & Pre-processing: Cleaning, noise removal, scan alignment.
• Compression (Encoding): G-PCC, V-PCC, or learned methods—the core IP battleground.
• Transmission/Storage: Efficient delivery over 5G or edge-cloud pipelines.
• Decompression (Decoding): Reconstructing the cloud for downstream use.
• Rendering & Application: Visualisation in headsets, autonomous driving stacks, or BIM software—where user value is realised.

Where it's heading

Globally, the point cloud compression market was valued at USD 1.23 billion in 2024 and is projected to reach USD 9.77 billion by 2033, a 22.7% CAGR (Point Cloud Compression Market Research Report 2033). Three shifts are shaping the space.

• AI-based learned compression is gaining traction, with open-source repositories cataloguing dozens of neural methods (awesome-learned-point-cloud-compression).
• Demand is surging from autonomous vehicles, construction, and healthcare, where 3D data volumes are exploding (Point Cloud Compression Market Research Report 2033).
• MPEG's G-PCC and V-PCC standards are solidifying, creating a stable baseline for interoperability and chip-level implementation (An Introduction to Point Cloud Compression Standards).

The opportunity in India

India's patent base in point cloud compression is notable—146 patents mapped in our dataset—yet no patent-holding startups appear. This suggests a pool of research output, likely from academia or large corporates, that has not yet been spun out into ventures.

Our data lists no deep-tech companies explicitly referencing point cloud compression in their profiles. That does not mean the technology is absent; it is likely embedded inside autonomous vehicle, AR/VR, or geospatial startups that describe themselves differently. Still, the absence of a dedicated PCC startup signals a wide-open field.

The gap between a steady patent stock and zero visible startup activity points to an opportunity: building product companies around G-PCC/V-PCC implementations, learned compression IP, or application-specific codecs for India's growing autonomous and smart-city deployments. No sector-specific funding rounds were captured, underscoring the early-stage nature of the commercial ecosystem.

India signal: patents, startups, capital

Our dataset maps 146 Indian patents to point cloud compression, with steady momentum. Because Indian patents remain confidential for about 18 months after filing, the most recent two years are understated; the count should be read as a stock, not a trend.

On the startup side, the picture is thin. No patent-holding startups were identified, and our broader company scan found zero deep-tech firms that explicitly mention point cloud compression in their profiles. This does not mean no Indian company works on the technology—many may use it without branding themselves around it—but it does indicate that dedicated PCC startups are absent from our radar.

No funding rounds linked to this technology were captured in our data. The combination of a solid patent base and a near-empty startup landscape suggests that point cloud compression in India is still a research-stage opportunity waiting for its first commercial champions.

In our data

Sources

• An Introduction to Point Cloud Compression Standards ↗
• What's new in Point Cloud Compression? ↗
• MPEG Point Cloud Compression – The public information on MPEG ... ↗
• Cloud-Based Supply Chain Transformation in Manufacturing ↗
• A cloud-based supply chain management system: effects ... ↗
• Cloud Supply Chain Management Market Size Report, 2030 ↗
• Point Cloud Compression Market Research Report 2033 ↗
• 3D Point Cloud Processing Software Market ↗