Perceiving the dynamics
of moving objects in complex scenarios is crucial for smart monitoring and safe
navigation, thus a key enabler for intelligent supervision and autonomous
driving. A variety of research has been developed to detect and track moving
objects from data collected by optical sensors and/or laser scanners while most of them concentrate on certain type of
objects or face the problem of lacking motion cues. In this thesis, we present a data-driven, model-free
detection-based tracking approach for tracking moving objects in urban scenes
from time sequential point clouds obtained via state-of-art Doppler LiDAR,
which can not only collect spatial information (e.g. point clouds) but also
Doppler images by using Doppler-shifted frequencies. In our approach, we first
use Doppler images to detect moving points and
determine the number of moving objects, which are then completely segmented via
a region growing technique. The detected objects are then input to the tracking session which is based on Multiple
Hypothesis Tracking (MHT) with two innovative extensions. One extension is that
a new point cloud descriptor, <i>Oriented
Ensemble of Shape Function (OESF)</i>, is proposed to evaluate the structure
similarity when doing object-to-track association in MHT. Another extension is
that speed information from Doppler images is used to predict the dynamic state
of the moving objects, which is integrated into MHT to improve the estimation of dynamic state of moving objects. The proposed approach has been tested on datasets
collected by a terrestrial Doppler LiDAR and a mobile Doppler LiDAR <a>separately</a>. The quantitative evaluation of detection and
tracking results shows the unique advantages of the Doppler LiDAR and the
effectiveness of the proposed detection and tracking approach.<br>
| Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/8038964 |
| Date | 11 June 2019 |
| Creators | Yuchi Ma (6632270) |
| Source Sets | Purdue University |
| Detected Language | English |
| Type | Text, Thesis |
| Rights | CC BY 4.0 |
| Relation | https://figshare.com/articles/Moving_Object_Detection_And_Tracking_With_Doppler_LiDAR/8038964 |
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