Dissertation > Excellent graduate degree dissertation topics show

Research on Moving Object Detection and Tracking Algorithms Based on Video Image

Author: ZhangRuiJuan
Tutor: LuHuChuan
School: Dalian University of Technology
Course: Signal and Information Processing
Keywords: Moving Object Detection Head Localization Mean Shift Tracking Kalman Filter Tri-tracking algorithm
CLC: TP391.41
Type: Master's thesis
Year: 2008
Downloads: 504
Quote: 7
Read: Download Dissertation

Abstract


Video surveillance system(VSS) is the main trend of modern defence system because of its visibility, convenience and abundance in content and has been widely used in many fields where a real-time surveillance is needed, such as national defense, traffic control, the intelligent public security and so on. Nowadays, VSS still depends on manual operation, which wastes resources and affects the efficiency, so studying the typical algorithms used in video surveillance and designing an intelligent video surveillance system is very important.Moving object detection and tracking are important parts of video monitor system and play important roles to other topics’ progress in computer vision. So how to detect and track object steadily, real-timely and effectively, becomes an important problem that needs to be paid attention and researched. The paper studied the key technologies of the field based on the current research achievements and mainly studied about the technologies on human object detection, segmentation and tracking.During object detection, several object foreground detection algorithms widely used are introduced, and their performances are analyzed. During object localization and segmentation, due to head contours similar to circles seen from the video sequences captured from vertical angular camera, the paper combines Freeman chain code and Random Sample Consensus (RANSAC) algorithm to estimate circle parameters and then localizes the human object quickly and accurately.During object tracking, in the light of current Mean Shift tracking algorithm’s drawbacks, Kalman filter and Mean Shift tracking algorithm integrating with color, texture and motion information is proposed and its tracking performance has been improved than before. Aiming at the posture’s significant change of a single object, a novel tracking algorthim based on RGB histogram feature, LBP (Local Binary Pattern) histogram feature and PPBTF (Pixel-Pattern-Based Texture Feature) histogram feature, using the semi-supervised learning is proposed on the basis of machine learning theory.

Related Dissertations

  1. Algorithm Research on SINS/GPS Integrated Navigation Syste,V249.328
  2. Satellite Attitude Determination Based on Gyro and Star Sensor,V448.2
  3. Research on Transfer Alignment of the Missile Onboard the Aircraft,V249.322
  4. Maneuver Detection and Tracking with the Radar Rate Measurement,TN953
  5. Research on Visual Detection and Tracking of Mobile Robots,TP242.62
  6. Design of Gyro Stabilized Pod Control System,TP273
  7. Research and Application on Detection and Tracking of Object Based on Video Stream,TP391.41
  8. Two Wheel Electric Bicycle Self-balance Control Algorithm Research,TP273
  9. Research of Positioning Algorithm Based on Cellular System,TN929.53
  10. Pedestrian Tracking Based on Multiple Laser Scanners,TP391.41
  11. Development and Application Research on a Video-based Motion Tracking and Analysis System for Animals,TP391.41
  12. Robot Localization in Fusion with Vision and Inertial Navigation,TP242
  13. Sensor Data Transmission and Processing of Inertia Motion Capture System,TP212
  14. AUV Integrated Navigation Algorithm Study and System Implementation,U666.1
  15. Research on Key Techniques of Indoor Wireless Sensor Network Tracking,TN929.5
  16. Research on Filtering for Local Strongly Coupled Systems,TN713
  17. Research on Key Techniques for Large Transport Vehicle Platform Autonomous Positioning,TH22
  18. Structural constraints of the dynamic PET image reconstruction,TP391.41
  19. Outside Radiant Passive Location and Tracking,TN953
  20. Driverless smart car moving target detection and tracking,TP391.41
  21. Embedded target detection and tracking system design and algorithm implementation,TP391.41

CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
© 2012 www.DissertationTopic.Net  Mobile