Pedestrians Detection Based on Laser Scanner and Camera Sensors For Unmanned Ground Vehicle : Pedestrians Detection Based on Laser Scanner and Camera Sensors For Unmanned Ground Vehicle

다국어 초록 (Multilingual Abstract)

In this thesis, we propose the idea to develop a real time rapid detecting pedestrians and measure the distance between vehicle and pedestrians based on laser scanner and camera data fusion for an unmanned ground vehicle system (UGV). The fast speed reflecting of laser’s beams provided an accurate range to compute the distance of any objects which appears in front. And image that captured from camera is used to classify shapes of object. First, laser scanner point data is clustered into segments, each of that indicates a candidate position of pedestrian. Then because of laser and image frames are different, Inverse Perspective Mapping (IPM) Algorithm is used to transform image plane into real world plan for matching with laser frame to form regions of interest (ROI) on the image. Once ROI is defined, Finally pedestrians could be extracted by using Support Vector Machine (SVM) classifier on Histogram of Oriented Gradient (HOG) features. The proposed system is tested on standard x86 machine and gives good real time performance.

목차 (Table of Contents)

• Chapter 1. Introduction = 1
• 1.1. Background and Motivation = 1
• 1.2. Contribution to Knowledge = 3
• 1.3. Problem Statement = 4
• 1.4. Approach = 5
• 1.5. Thesis Organization = 7
• Chapter 2. Related Works = 9
• 2.1. Autonomous Navigation Research = 9
• 2.2. Vision Based Obstacle Detection = 14
• 2.3. Real Time Distance Determination using IPM = 18
• Chapter 3. Sensors Overview = 22
• 3.1. Camera Sensor = 22
• 3.1.1. Pinhole Camera Model = 22
• 3.1.2. Stereo Camera Model = 24
• 3.2. Laser Scanner Sensor = 25
• 3.2.1 About Laser Scanner = 26
• Chapter 4. Equipment and Software = 27
• 4.1. Hardware and Software = 27
• 4.2. Devices Equipped on the Vehicle = 28
• Chapter 5. Implementations = 31
• 5.1. Overall System Flowchart = 31
• 5.2. Procedure Overview = 32
• 5.3. Feature Extraction from Laser Scanner = 33
• 5.4. Coordinates Correspondence between Laser and Camera = 34
• 5.5. Determine ROI on Image Plane Respect to Laser Coordinate = 38
• 5.6. Pedestrian validation on ROIs = 39
• Chapter 6. Conclusion = 46
• 6.1. Future Work = 46
• References = 47