Previous Work: Most of the previous work dealt with frontal faces. [1] used clustering to generate face and non-face prototypes. For each test pattern they calculate the distances between the pattern and the prototypes. These distances form the input to a multi-layer perceptron which classifies the pattern into a face and non-face class. In [2] they used a Support Vector Machine (SVM) with a 2n...

Face detection is concerned with finding whether or not there are any faces in a given image (usually in gray scale) and, if present, return the image location and content of each face. This is the first step of any fully automatic system that analyzes the information contained in faces (e.g., identity, gender, expression, age, race and pose). While earlier work dealt mainly with upright fronta...

This paper proposes a scale invariant face detection method which combines higher-order local autocorrela-tion (HLAC) features extracted from a log-polar transformed image with Linear Discriminant Analysis for \face" and \not face" classiication. Since HLAC features of log-polar image are sensitive to shifts of a face, we utilize this property and develop a face detection method. HLAC features ...

Automatic content-based analysis and indexing of broadcast news recordings or digitized news archives is becoming an important tool in the framework of many multimedia interactive services such as news summarization, browsing, retrieval and news-on-demand (NoD) applications. Existing approaches have achieved high performance in such applications but heavily rely on textual cues such as closed c...

Face Detection for Skintone Images Using Wavelet and Texture Features Written by Administrator Wednesday, 16 March 2011 09:26 Last Updated Monday, 21 March 2011 06:50 Images with Skin-tone regions pose new challenges in face detection problem. Paper presents a novel detection algorithm that uses a combination of colour spaces and edgedetection for segmentation followed by texture feature analy...

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...

Successful face detection and facial feature extraction is crucial for for a variety of applications, including speech recognition and fatigue monitoring. Detecting and tracking faces in a moving automobile is challenging because of a variety of reasons. Among these reasons are changing poses, extreme lighting changes and shadowing. In this paper, we investigate two approaches for shadow compen...

Disaster events like the attack on the World Trade Center in New York City in 2001 and the earthquake in Haiti in 2010 result in a desperate need for family and friends to obtain information about missing people. This can be facilitated by automatically extracting textual descriptors of patients from images taken at emergency triage centers. We show that existing face detection algorithms, a ne...

In this paper we present a method of automatic color correction of face images and its application in a face detection algorithm. The color correction method is based on the phenomenon of color constancy observed in human visual perception. This technique is further applied in a face detection system, which draws upon the analogy to the parallel organization of visual neural pathways, the magno...

Face Detection for Skintone Images Using Wavelet and Texture Features Written by Administrator Wednesday, 16 March 2011 09:26 Last Updated Monday, 21 March 2011 06:50 Images with Skin-tone regions pose new challenges in face detection problem. Paper presents a novel detection algorithm that uses a combination of colour spaces and edgedetection for segmentation followed by texture feature analy...