Explore human detection, tracking, and segmentation techniques in surveillance video through this doctoral dissertation defense. Delve into scene-specific learning approaches, including DPM human detectors, superpixel-based Bag-of-Words classifiers, and part-based person-specific SVM models. Discover methods for handling occlusions in detection and tracking, as well as separating human and background superpixels using Conditional Random Fields. Learn about leveraging spatio-temporal constraints with tracklet-based Gaussian Mixture Models and multi-frame graph optimization. Examine the development of NONA, an efficient real-time tracking system for high-definition surveillance video, implemented using Intel Threading Building Blocks. Gain insights into Fast Fourier Transform-based normalized cross-correlation, Adaptive Template scaling, and Local Frame Differencing techniques for improved tracking performance.
Human Detection, Tracking and Segmentation in Surveillance Video
University of Central Florida via YouTube
Overview
Syllabus
Motivation
Video Surveillance Tasks
Outline
Problems
Initial Detection
Training and Classification
Iteratively Learning
Superpixel Segmentation
Bag-of-Words
Qualitative Results
From Detection to Tracking
Part-based Model in Tracking
Features and Classifiers
Data Association
Proposed Method
DPM with Occlusion Handling
Occlusion handling Results
Occlusion Handling in Tracking
Occlusion Reasoning Results
Quantitative Results -- Town Center
Boston Airport
Parking Lot 1
Parking Lot dataset
From Detection to Segmentation
Human Detection
Background Gaussian Mixture Model (GMM)
Part-based Detection Potential
Graph Optimization
Initial Results
Multi-frame Segmentation
Obtaining Tracklets
Multi-frame CRF Optimization
Datasets and Groundtruth
Comparison with Background Subtraction
Segmentation Results (by frame)
For Real-World Application
Objective: Tracking
Multi-threaded Implementation
Tracking Overview
Adaptive Scaling
Local Frame Differencing
Summary
Dissertation Conclusion
Future Work
Publication
Taught by
UCF CRCV
