Fundamentals of digital image processing
Fundamentals of digital image processing
Probabilistic Visual Learning for Object Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Neural Network-Based Face Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Detecting Faces in Images: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Detection in Color Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition Using Line Edge Map
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition: Features Versus Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Face Detection Using the Hausdorff Distance
AVBPA '01 Proceedings of the Third International Conference on Audio- and Video-Based Biometric Person Authentication
Experiences with a mobile robotic guide for the elderly
Eighteenth national conference on Artificial intelligence
Face Detection Using Mixtures of Linear Subspaces
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
A Robust Approach to Face and Eyes Detection from Images with Cluttered Background
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 1 - Volume 1
Robust Face Detection at Video Frame Rate Based on Edge Orientation Features
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Automatic extraction of head and face boundaries and facial features
Information Sciences—Informatics and Computer Science: An International Journal - Special issue: Informatics and computer science intelligent systems applications
Automatic Facial Feature Detection and Location
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
Components for face recognition
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Face detection using quantized skin color regions merging andwavelet packet analysis
IEEE Transactions on Multimedia
Facial feature localization based on an improved active shape model
Information Sciences: an International Journal
A method of illumination compensation for human face image based on quotient image
Information Sciences: an International Journal
Real-time face tracking system using adaptive face detector and Kalman filter
HCI'07 Proceedings of the 12th international conference on Human-computer interaction: intelligent multimodal interaction environments
Image-based facial sketch-to-photo synthesis via online coupled dictionary learning
Information Sciences: an International Journal
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In this paper, an effective method of facial features detection is proposed for human-robot interaction (HRI). Considering the mobility of mobile robot, it is inevitable that any vision system for a mobile robot is bound to be faced with various imaging conditions such as pose variations, illumination changes, and cluttered backgrounds. To detecting face correctly under such difficult conditions, we focus on the local intensity pattern of the facial features. The characteristics of relatively dark and directionally different pattern can provide robust clues for detecting facial features. Based on this observation, we suggest a new directional template for detecting the major facial features, namely the two eyes and the mouth. By applying this template to a facial image, we can make a new convolved image, which we refer to as the edge-like blob map. One distinctive characteristic of this map image is that it provides the local and directional convolution values for each image pixel, which makes it easier to construct the candidate blobs of the major facial features without the information of facial boundary. Then, these candidates are filtered using the conditions associated with the spatial relationship of the two eyes and the mouth, and the face detection process is completed by applying appearance-based facial templates to the refined facial features. The overall detection results obtained with various color images and gray-level face database images demonstrate the usefulness of the proposed method in HRI applications.