Table of Contents

Mega mapping service

Spatial mapping is the core of Mega cloud services, positioned as the central hub in the entire Mega workflow. It receives collected data from the physical world and outputs digital assets required for application development.

The following shows the position of spatial mapping in the entire Mega workflow:

flowchart LR

A[Data collection] --> B>Build Mega Block map] --> C[Mega localization]

Feature introduction

EasyAR Mega adopts a fully cloud-based automated processing workflow. Developers don't need to run any complex mapping algorithms locally. Simply upload compliant video data, and the cloud cluster can automatically complete the following tasks:

  • Feature extraction: Identify key visual features in the environment (such as corner points, textures).

  • Spatial reconstruction: Calculate 3D spatial coordinates of feature points to generate spatial data.

  • Loop closure detection: Automatically identify loop closures to eliminate accumulated errors.

  • Georeferencing: Align local coordinate systems to the global geographic coordinate system using GNSS data.

  • Multi-map fusion: Support merging multiple independent collection blocks into a complete map (for large-scale scenes).

Block mapping workflow

Organize mapping tasks by creating and managing mapping projects. After successful mapping, Blocks are generated.

flowchart LR

A[Mapping project] --> B[Mapping task] --> C[Mapping result Block]
  • Mapping project: Used to organize and manage related mapping tasks
  • Mapping task: Performs specific mapping operations
  • Block: The final product of successful mapping

Different types of mapping tasks

Depending on your scene size and collection strategy, Mega provides four types of mapping tasks. Please create the corresponding type based on actual conditions:

Regular single-map task

  • Applicable scenarios: Small to medium-sized scenes, single collection covering the entire scene
  • Typical cases: Single-floor malls, restaurants, single-floor offices, exhibition halls, parks, etc.
  • Collection device: GoPro Max/Max2 panoramic camera
  • Steps: Create regular single-map task

Large-scale multi-map fusion task

  • Applicable scenarios: Very large scenes, multi-floor, multi-region connected scenes
  • Typical cases: Large shopping centers (connecting floors), commercial districts (connecting indoor/outdoor), university campuses (connecting multiple buildings), etc.
  • Collection device: GoPro Max/Max2 panoramic camera
  • Steps: Create large-scale multi-map fusion task

Small-scale mobile collection task

  • Applicable scenarios: Small-scale scenes, compact spaces
  • Typical cases: Rooms, shops, exhibition halls, etc.
  • Collection device: iPhone / ARCore Android phone
  • Steps: Create small-scale mobile collection task

Object mobile collection task

  • Applicable scenarios: Single objects
  • Typical cases: Exhibits, equipment, merchandise, etc.
  • Collection device: iPhone / ARCore Android phone
  • Steps: Create object mobile collection task

Mapping status description

In the development center Block mapping interface, you'll see real-time status of mapping tasks. Understanding these statuses helps assess task progress:

Mapping status Description Recommended action
Under review Manual video review in progress Wait for review completion
Queued Waiting for available server resources Wait for server allocation
Generating Server processing in progress Wait for mapping completion
Task completed Mapping succeeded View mapping results
Generation failed Mapping failed Troubleshoot

View mapping results

After mapping completes, further inspect results to confirm if they meet requirements.

Troubleshooting mapping failures

When a mapping task fails, follow these troubleshooting steps:

  • View mapping report: View mapping report, find solutions based on report information.
  • Reference troubleshooting: Consult the Mapping failure troubleshooting guide for common solutions.
  • Contact technical support: If unresolved, contact EasyAR staff and provide the JobID from the mapping report for quick issue identification.

Next steps