A Combined Voxel and Particle Filter-Based Approach for Fast Obstacle Detection and Tracking in Automotive Applications
| Autor: | Javier Sanchez-Medina, Nestor Morales, Jonay Toledo, Leopoldo Acosta |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
050210 logistics & transportation
Computer science business.industry Mechanical Engineering 05 social sciences Point cloud Tracking system 02 engineering and technology Tracking (particle physics) Object detection Computer Science Applications Odometry Video tracking Motion estimation 0502 economics and business Automotive Engineering 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer vision Artificial intelligence business Particle filter |
| Zdroj: | IEEE Transactions on Intelligent Transportation Systems. 18:1824-1834 |
| ISSN: | 1558-0016 1524-9050 |
| DOI: | 10.1109/tits.2016.2616718 |
| Popis: | In this paper, a new method for real-time detection, motion estimation, and tracking of generic obstacles using just a 3-D point cloud and odometry information as input is presented. In this approach, a simplification of the world is done using voxels, supported by a particle filter-based 3-D object segmentation and a motion estimation scheme. That combination of techniques leverages a fast and reliable object detection, providing also motion speed and direction information. Four detailed studies have been performed in order to assess the suitability of the method, two of them related to the parameterization of the method and its input point cloud. Another one compares the tracking and detection results with other state-of-the-art methods. Last tests are intended for the characterization of the execution times required. Results are encouraging, with a high detection rate, low error rate, and real-time capable computing performance. In the attached video, it is possible to observe the behavior of the method, both using a stereovision and a light-detection and ranging generated point clouds as an input. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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