Enhanced 3D Capabilities for Efficient Computer Vision Annotations

Case Study

Enhanced 3D Capabilities for Efficient Computer Vision Annotations

How LogicHive integrated 3D functionality into a widely used annotation tool, allowing users to seamlessly switch between 2D and 3D environments for advanced data handling.

Industry

Time Frame

2 Months

Services We offer

Web Apps

Python Development

3D Annotation

About the client

The client, a global leader in semiconductor technology and innovation, is renowned for its contributions to the industry, including significant open-source initiatives.

Problem Statement

The client wanted to enhance their annotation tool by adding 3D support, crucial for industries working with autonomous systems, robotics, and complex datasets.

The challenge was to build a seamless experience for users transitioning between 2D and 3D environments, maintaining ease of use while adding features like point cloud annotation with supporting additional formats for tool versatility.

Our role was to integrate 3D capabilities into a tool that already excelled in 2D annotation, without disrupting the user experience.

The Challenges

Ensuring Backward Compatibility with 2D Code

Maintaining full functionality of the existing 2D features while integrating new 3D capabilities without causing disruptions or regressions

Transition Between 2D and 3D

Ensuring a smooth, intuitive switch between 2D and 3D modes without compromising the user experience.

Managing Open-Source Code Reviews

Coordinating feedback from numerous open-source reviewers while maintaining development pace and ensuring consensus on key changes.

Handling Large Point Cloud Data

Efficiently processing and rendering large, complex point cloud datasets while maintaining tool performance.

Approach

LogicHive conducted a thorough evaluation of the tool to identify the optimal approach for integrating 3D rendering while preserving its simplicity and accessibility.

The goal was to provide users with a seamless experience for managing point cloud data, switching viewpoints, and converting between various data formats, all while building on the tool’s established strengths in 2D.

This ensures the tool remains a leader in the rapidly evolving field of computer vision.

The Solution

3D Rendering & Point Cloud Annotation: Integrated advanced 3D support, enabling users to annotate and navigate through point clouds with ease. Users can now switch seamlessly between 2D and 3D views to better visualize and annotate complex datasets.
Referential Image Mapping: Providing context for point cloud data, improving the precision and reliability of annotations.
Enhanced Viewpoints: Added multiple viewpoints to help users better annotate 3D data, ensuring accuracy and reducing annotation time.
Efficiency Tools: Added keyboard shortcuts and accessibility features to streamline the workflow, making large-scale annotations more manageable and efficient.
Drag-and-Drop Functionality: Enhanced the interface with a user-friendly drag-and-drop feature to simplify the annotation process across both 2D and 3D modes.
Data Interchange Formats: Implemented support for popular formats like Velodyne and KITTI, allowing compatibility with various tools and systems.