Improving shape-based face recognition by means of a supervised discriminant Hausdorff distance
نویسندگان
چکیده
This paper introduces a supervised discriminant Hausdorff distance that fits into the framework for automatic face analysis and recognition proposed in [1]. Our proposal relies solely on face shape variation contrarily to most of the successful model-based approaches, and results show comparable performance to them. The whole framework is based in a new set of Hausdorff measures and defines face-shape based similarity measures and supervised criteria to add discriminant capabilities to the Hausdorff distance. The paper presents experimental results supporting the proposed methodologies.
منابع مشابه
Supervised Feature Extraction of Face Images for Improvement of Recognition Accuracy
Dimensionality reduction methods transform or select a low dimensional feature space to efficiently represent the original high dimensional feature space of data. Feature reduction techniques are an important step in many pattern recognition problems in different fields especially in analyzing of high dimensional data. Hyperspectral images are acquired by remote sensors and human face images ar...
متن کاملA Supervised Modification of the Hausdorff Distance for Visual Shape Classification
Hausdorff distance is a deformation tolerant measure between two sets of points. The main advantage of this measure is that it does not need an explicit correspondence between the points of the two sets. This paper presents the application to automatic face recognition of a novel supervised Hausdorff-based measure. This measure is designed to minimize the distance between sets of the same class...
متن کاملHuman Face Recognition Using a Spatially Weighted
The edge map of a facial image contains abundant information about its shape and structure, which is useful for face recognition. To compare edge images, Hausdroff distance is an efficient measure that can determine the degree of their resemblance, and does not require a knowledge of correspondence among those points in the two edge maps. In this paper, a new modified Hausdorff distance measure...
متن کاملFace Recognition by Cognitive Discriminant Features
Face recognition is still an active pattern analysis topic. Faces have already been treated as objects or textures, but human face recognition system takes a different approach in face recognition. People refer to faces by their most discriminant features. People usually describe faces in sentences like ``She's snub-nosed'' or ``he's got long nose'' or ``he's got round eyes'' and so like. These...
متن کاملEmotion Recognition from Decision Level Fusion of Visual and Acoustic Features using Hausdorff Classifier
The emotions are generally measured by analyzing either head movement patterns or eyelid movements or face expressions or all the lasts together. Concerning emotion recognition visual sensing of face expressions is helpful but generally not always sufficient. Therefore, one needs additional information that can be collected in a non-intrusive manner in order to increase the robustness. We find ...
متن کامل