Rotation Invariant Tracking-Learning-Detection System

Rotation Invariant Real-time Face Detection and Recognition System

In this report, a face recognition system that is capable of detecting and recognizing frontal and rotated faces was developed. Two face recognition methods focusing on the aspect of pose invariance are presented and evaluated | the whole face approach and the component-based approach. The main challenge of this project is to develop a system that is able to identify faces under di erent viewin...

Rotation Invariant Real - time Face Detection and Recognition System

Rotation Invariant Neural Network-Based Face Detection

The system (see Figure 2) uses a neural network, called a “router”, to analyze each window of the input before it is processed by a “detector” network. If the window contains a face, the router returns the angle of the face. The window can then be “derotated” to make the face upright. The derotated window is then passed to the detection network, which decides whether a face is present. If a non...

Rotation Invariant Content-Based Image Retrieval System

The emergence of multimedia technology and the rapid growth in the number and type of multimedia assets controlled by several entities, yet because the increasing range of image and video documents showing on the Internet, have attracted vital analysis efforts in providing tools for effective retrieval and management of visual data. So the need for image retrieval system arose. Out of many exis...

Fast Rotation Invariant Object Detection with Gradient based Detection Models

Accurate object detection has been studied thoroughly over the years. Although these techniques have become very precise, they lack the capability to cope with a rotated appearance of the object. In this paper we tackle this problem in a two step approach. First we train a specific model for each orientation we want to cover. Next to that we propose the use of a rotation map that contains the p...