We examine how to identify video shots with at least two humans using only detected face information. While face detection is much more reliable than shape based people classification in broadcast video, one particular difficulty is that, when there are several humans in an image, the accuracy of face detection is usually significantly degraded, which leads to poor performance in identifying sh...

This paper describes the use of sensors in intelligent tutors to detect students' affective states and to embed emotional support. Using four sensors in two classroom experiments the tutor dynamically collected data streams of physiological activity and students’ self-reports of emotions. Evidence indicates that state-based fluctuating student emotions are related to larger, longer-term affecti...

Human detection under occlusion is a challenging problem in computer vision. We address this problem through a framework which integrates face detection and person detection. We first investigate how the response of a face detector is correlated with the response of a person detector. From these observations, we formulate hypotheses that capture the intuitive feedback between the responses of f...

This paper describes a simple and efficient method to make template-based object classification invariant to in-plane rotations. The task is divided into two parts: orientation discrimination and classification. The key idea is to perform the orientation discrimination before the classification. This can be accomplished by hypothesizing, in turn, that the input image belongs to each class of in...

In order to detect faces in pictures presenting difficult real-world conditions such as dark background or backlighting, we propose a new method which is robust to varying illuminations and which automatically adapts itself to these lighting changes. The proposed face detection technique is based on an efficient AdaBoost super-classifier and relies on multiple features, namely, the global inten...

The aim of this paper is to detect faces in noisy images. All the test images contain faces with uniform background. The Hit-Miss transform is used to detect the boundaries of the objects and eliminate the effect of noise. Two filters are cascaded in a special way as to handle high levels of noise. An application for face detection in noisy conditions is presented. The algorithm is implemented ...

A robust and e$cient human face detection system that can detect multiple faces in complex backgrounds is presented in this paper. The proposed system consists of two primary parts. The "rst part is to search for the potential face regions. The second part is to perform face verixcation. Our system can conquer di!erent sizes, di!erent lighting conditions, varying pose and expression, and noise ...

This paper presents progress toward an integrated, robust, real-time face detection and demographic analysis system. Faces are detected and extracted using the fast algorithm recently proposed by Viola and Jones [16]. Detected faces are passed to a demographics classifier which uses the same architecture as the face detector. This demographic classifier is extremely fast, and delivers error rat...

Integral projections can be used to model the visual appearance of human faces. In this way, model based detection is done by fitting the model into an unknown pattern. Thus, the key problem is the alignment of projection patterns with respect to a given model of generic face. We provide an algorithm to align a 1-D pattern to a model consisting of the mean pattern and its variance. Projection m...

Human face processing techniques for broadcast video, including face detection, tracking, and recognition, has attracted a lot of research interest because of its value in various applications, such as video structuring, indexing, retrieval, and summarization. The main reason for this is that the human face provides rich information for spotting the appearance of certain people of interest, suc...