Dissertation > Excellent graduate degree dissertation topics show
Research on Moving Object Detection and Tracking in Complex Condition
Author: LiuRui
Tutor: SunHan
School: Nanjing University of Aeronautics and Astronautics
Course: Applied Computer Technology
Keywords: Moving target detection and tracking Multi - feature fusion modeling Particle filter Line scan DSP transplant Optimization
CLC: TP391.41
Type: Master's thesis
Year: 2009
Downloads: 152
Quote: 1
Read: Download Dissertation
Abstract
|
Moving target detection and tracking is a key topic in the computer vision -disciplinary research . Has a wide range of applications such as video surveillance, security suspects under strict surveillance , weaponry . Through the joint efforts of the researchers at home and abroad over the years , moving target detection and tracking technology has been developed by leaps and bounds , and made ??a lot of ground - breaking research . But in actual complex environment of the scene , the illumination changes , object occlusion , the presence of shadow interference , deformation effects , presented new challenges to the technology . To solve these problems well , and to achieve the requirements of practical applications , the need to design real-time and robustness of the new algorithm both . This paper in-depth study of certain core algorithm , and made ??a new attempt on this basis , this paper is as follows : depth study of the classical methods of detection and tracking of moving targets at home and abroad , and experiments to understand the advantages and disadvantages of each and suitable application conditions. On this basis , the proposed combined modeling based on multi-feature target Mean-Shift and Particle Filter tracking algorithm . The goal modeling combines general target characteristics as color , edge , texture , and also draw on the concept of structural similarity (SSIM) image quality evaluation in the field of research , the structural information extracted target characteristics as the fourth fusants . Improved multi- feature fusion method , the robustness of the target model . Final tracking of moving targets in MSPF (Mean-Shift Particle Filter) improved tracking framework . The algorithm to track accurately verified by experiments . Proposed a target extraction algorithm based on line scan , the algorithm for progressive scan image , extracted directly target chain code tracking , do not need the full map . The algorithm combined in the development of embedded DSP DMA double buffering technology , can greatly reduce the overhead of algorithm time . The multi - feature fusion the MSPF target tracking algorithm transplant to the the ADSP BF561 development platform , a number of issues to solve transplantation in image format conversion . Combined target extraction algorithm based on line scan , optimize the realization of the target tracking algorithm in the platform . Transplant based on the C language and assembly-level code optimization , to further enhance the efficiency of algorithm execution , and ultimately to meet the requirements of real-time target tracking applications .
|
Related Dissertations
- Research on Cooperative Orbit Determination in Satellite Network Based on Multi-Agent System Theory,V474
- The Maneuvering Target Tracking Research Based on VRPF,TN957.52
- The Research of 3D Human Motion Capture Based on Reference Points,TP391.41
- Research on the Theory of Visual Object Tracking Based on Particle Filter for Autonomous Robot,TP242
- Space Infrared Target Simulation and Application of Target Trace,TP391.41
- Detection and Tracking of Moving Object in Complex Background,TP391.41
- Moving Objects Detection and Tracking Using Fisheye Camera,TP391.41
- The Research on the Target Localization and Tracking Based on WSN,TN929.5
- The Study of Moving Object Detection and Tracking Algorithm Based on Image Information,TP391.41
- The Research on Localization and Target Tracking in Wireless Sensor Network,TN929.5
- AUV Integrated Navigation Algorithm Study and System Implementation,U666.1
- Architectural Optimizations for Particle Filters,TN713
- Wheeled humanoid robot navigation and path planning,TP242
- Petri net -based network intrusion detection system Research and Implementation,TP393.08
- GPU-accelerated particle filter PET image reconstruction algorithm,TP391.41
- Particle filter based multi-component FM fixed distance reconnaissance signal separation and parameter extraction,TN911.7
- Based on mid-level visual features and high-level structural information complementary target tracking model,TP391.41
- Target Tracking Based on Particle Filter Algorithm and DirectShow realized,TP391.41
- Based on Particle Filter and reliable visual tracking technology,TP391.41
- Distributed Microphone Array Tracking Algorithm,TN912.3
- Based on the theory of multi-target tracking FISST Research,TN953
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
|