GRIP Globally optimal robust 3D point set registration

The aim of this thesis is to provide a robust and globally optimal method for rigid point set registration in the presence of outliers and structured noise. The registration of 2D or 3D point sets is a common problem in computer vision [9], with applications that include aligning MRI/CT scans, and simultaneous localization and mapping (SLAM) in...

Collision Avoidance for Predefined C-arm Trajectory using 3D Depth Measurements

Human-robot collaborative act is obvious nowadays in a modern intervention room. It is very important to ensure the safety of the patient along with other personnel in the operation theater and prevent damages to the equipment during an intervention. Due to the complex environment and multiple unknown dynamic objects in the room, vision-based...

High-Speed Object Detection: Design, Study and Implementation of a Detection Framework using Channel Features and Boosting

In this thesis we design, implement and study a high-speed object detection framework. Our baseline detector uses integral channel features as object representation and AdaBoost as supervised learning algorithm. We suggest the implementation of two approximation techniques for speeding up the baseline detector and show their effectiveness by...

Vision-based 3D Human Motion Analysis in a Hierarchical Way

In the last decade, computer vision has drawn more and more attention because of its potential applications in our daily lives, such as health care, education, safety, and training. However the high complexity of many of the vision-based approaches hinders their practical applications, especially in applications where immediate feedback is...

Multi-Scale Pattern Recognition for Image Classification and Segmentation

Scale is an important parameter of images. Different objects or image structures (e.g. edges and corners) can appear at different scales and each is meaningful only over a limited range of scales. Multi-scale analysis has been widely used in image processing and computer vision, serving as the basis for many high-level image analysis systems....

Crowd control by multiple cameras

One of the goals of the crowd control project at Delft University of Technology is to detect and track people during a crisis event, classify their behavior and assess what is happening. The assumption is that the crisis area is observed by multiple cameras (fixed or mobile). The cameras sense the environment and extract features such as the...