Table of Contents

Mega scene updates

Incremental updates and lossless full updates are advanced features provided by EasyAR Mega to handle scene changes. They maintain the original coordinate system unchanged after scene updates, ensuring that developed AR content positions do not shift, thereby significantly improving application development efficiency.

Incremental update

The incremental update feature allows developers to append new video data to an already constructed spatial map. Cloud algorithms attempt to "stitch" feature points from the new data into the coordinate system of the old map, achieving map updates without recreating an entirely new Block spatial map.

Related features:

Lossless full update

The lossless full update feature allows developers to comprehensively update the entire scene using newly collected data while maintaining the original coordinate system. Cloud algorithms reconstruct the spatial map based on new video data, ensuring that developed AR content positions do not shift, achieving seamless updates.

Related features:

Feature comparison

Feature Incremental update Lossless full update
Applicable scenario Partial area updates or supplements Comprehensive updates for entire scenes
Collection device GoPro Max panoramic camera GoPro Max panoramic camera
Data source Appends new video data to original map Re-builds using newly collected data based on original map
Coordinate system preservation Yes Yes

Frequently asked questions

  • What are the differences between incremental update mapping, lossless full update mapping, and multi-map fusion mapping?
    Incremental update mapping: Adds new data to existing maps for partial area updates or supplements while maintaining the original coordinate system.
    Lossless full update mapping: Comprehensively updates the entire scene by re-mapping with newly collected data while preserving the original coordinate system. The updated spatial map contains only newly submitted data, not original data.
    Multi-map fusion mapping: Combines multiple independently collected area maps into a complete map, typically used for parallel collection of large-scale scenes.

  • Can incremental update mapping be used if the entire scene is completely renovated?
    No, algorithms cannot effectively match new videos with old map content. If parts of the space outside the renovated area remain unchanged, collect those unupdated areas together to enable feature fusion for incremental updates.

  • Will failed incremental or lossless full update mapping affect the original map?
    No. Regardless of mapping task success or failure, the original map remains unaffected. Successful mapping generates new map data without overwriting the original map.