Summary of Real-time 3d Object Detection Using Innovizone Lidar and Low-power Hailo-8 Ai Accelerator, by Itay Krispin-avraham et al.
Real-Time 3D Object Detection Using InnovizOne LiDAR and Low-Power Hailo-8 AI Accelerator
by Itay Krispin-Avraham, Roy Orfaig, Ben-Zion Bobrovsky
First submitted to arxiv on: 7 Dec 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper proposes a method for real-time 3D object detection using LiDAR sensors and low-power AI accelerators, which is crucial for autonomous driving applications. The proposed approach leverages the InnovizOne sensor’s high-quality point clouds to detect cars with high accuracy (0.91% F1 score) at a rate of approximately 5Hz on an Hailo-8 AI accelerator, comparable to running the same model on a powerful NVIDIA GeForce RTX 2080 Ti. This achievement represents a significant step towards more accessible autonomous driving technologies. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper shows how to use a special kind of sensor called LiDAR to detect objects in 3D space, which is important for self-driving cars. The sensor creates a 3D point cloud that helps the computer recognize and track objects like other cars. The researchers used a special AI chip called Hailo-8 to process this information quickly and accurately. They were able to detect cars in real-time with high accuracy using only a low-power chip, which is important for making self-driving cars more accessible. |
Keywords
» Artificial intelligence » F1 score » Object detection
