L. Wiskott, "Phantom faces for face analysis," Pattern Recognition 30(6), pp. 837--846, 1997.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....in the field of image analysis. There are many different problems and applications which base on the processing of such images. The tasks of facial image analysis include the face localization [15, 9] the recognition of human faces [12, 2, 13] and the analysis of mimics or facial expressions [16, 10, 14]. Applications exist, for instance, for access control of rooms and buildings [5, 7] the indexing of police mugshots [3] or medical tasks [1] Another important application results from object based image coding and transmission[6, 8] partially funded by DFG, SFB 603 TP B3 The analysis of ....

L. Wiskott. Phantom faces for face analysis. In Proc. IEEE Intern. Conf. on Image Processing, ICIP'97, Santa Barbara, pages III 308--311. IEEE, October 1997.

....in elastic graph matching that received much attention is the weighting of graph nodes according to their discriminatory power. Several methods have been proposed. For example, a Bayesian approach yields the more reliable nodes for gender identification, beard and glass detection in bunch graphs [16]. An automatic weighting of nodes according to their significance by employing local discriminants is proposed in [17] A weighted average of feature vector similarities by a set of coefficients that take September 30, 1999 DRAFT 3 into account the importance of each feature in assigning a test ....

....morphological dynamic link architecture (MDLA) is developed for frontal face authentication in this paper. During the training phase, a sparse rigid grid is placed over the facial region of the image of each person in the reference set. Instead of using either the magnitude [9, 17] or phase [16] responses of a bank of Gabor filters tuned to different orientations and scales, as proposed in the original dynamic link architecture, we employ the multiscale dilation erosion of the image by a structuring function [19] to derive a feature vector at each grid node. There are strong theoretical ....

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L. Wiskott, "Phantom faces for face analysis," in Lecture Notes in Computer Science: Computer Analysis of Images and Patterns (G. Sommer, K. Daniilidis, J. Pauli, Eds.), vol. 1296, pp. 480--487, 1997.

....that has received much attention is the weighting of graph nodes according to their discriminatory power. Several methods have been proposed in the literature. For example, a Bayesian approach yields the more reliable nodes for gender identification, beard and glass detection in bunch graphs [7]. An automatic weighting of the nodes according to their significance by employing local discriminants is proposed in [8] Frequently, linear projection algorithms are used to reduce the dimensionality of the feature vectors. The type of linear projection used in practice is influenced by the ....

L. Wiskott, "Phantom faces for face analysis," in Lecture Notes in Computer Science:Computer Analysis of Images and Patterns (G.Sommer, K. Daniilidis, J. Pauli, Eds.), vol. 1296, pp. 480--487, 1997.

....that has received much attention is the weighting of graph nodes according to their discriminatory power. Several methods have been proposed in the literature. For example, a Bayesian approach yields the more reliable nodes for gender identification, beard and glass detection in bunch graphs [11]. An automatic weighting of the nodes according to their significance by employing local discriminants is proposed in [2] The research reported in this paper has been carried out within the framework of the European ACTS M2VTS project. A weighted average of the feature vector similarities by a ....

L. Wiskott, "Phantom faces for face analysis," in Lecture Notes in Computer Science:Computer Analysis of Images and Patterns (G.Sommer, K. Daniilidis, J. Pauli, Eds.), vol. 1296, pp. 480--487, 1997.

....that has received much attention is the weighting of graph nodes according to their discriminatory power. Several methods have been proposed in the literature. For example, a Bayesian approach yields the more reliable nodes for gender identification, beard and glass detection in bunch graphs [15]. An automatic weighting of the nodes according to their significance by employing local discriminants is proposed in [2] A weighted average of the feature vector similarities by a set of coefficients that take into account the importance of each feature in assigning a test person to a specific ....

L. Wiskott, "Phantom faces for face analysis," in Lecture Notes in Computer Science:Computer Analysis of Images and Patterns (G.Sommer, K. Daniilidis, J. Pauli, Eds.), vol. 1296, pp. 480--487, 1997.

....with the help of statistical estimation methods (cf. Maurer von der Malsburg, 1996; Kr uger et al. 1998) Our system comes close to the natural model by needing only a small number of examples to handle the complex task of face recognition. This work has been described in short form in (Wiskott et al. 1997), from which portions have been adopted for this text. In the discussion we will compare our system to others and to our own previous work. 2 The System 2.1 Preprocessing with Gabor Wavelets The representation of local features is based on the Gabor wavelet transform; see Figure 1. Gabor ....

....We used various model and probe galleries with faces of different pose. Each model gallery contained 250 faces with just one image per person. We relied on the explicitly labeled pose identity instead of using our own pose recognition capability. Recognition results are shown in Table 1 (from Wiskott et al. 1997). Model Probe First rank First 10 ranks gallery images # # 250 fa 250 fb 245 98 248 99 250 hr 181 hl 103 57 147 81 250 pr 250 pl 210 84 236 94 249 fa 1 fb 171 hl 79 hr 44 18 111 44 171 hl 79 hr 249 fa 1 fb 42 17 95 38 170 hl 80 hr 217 pl 33 pr 22 9 67 27 217 pl 33 pr 170 hl 80 ....

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Wiskott, L. (1997). Phantom faces for face analysis. Pattern Recognition, 30(6):837--846.

....to compensate for the effect of rotation in depth. On a frontal pose gallery of 90 faces and half profile probe images an average improvement of the first rank recognition rate of 15 was achieved, from 36 without rotation to 50 and 53 with rotation, depending on which pose was rotated. In [10] the bunch graph technique has been used to fairly reliably determine facial attributes from single images, such as sex or the presence of glasses or a beard. If this technique was developed to extract independent and stable personal attributes, such as age, race, or sex, recognition from large ....

L. Wiskott, "Phantom faces for face analysis," Pattern Recognition, vol. 30, no. 6, pp. 837--846, 1997.

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L. Wiskott, "Phantom faces for face analysis," Pattern Recognition 30(6), pp. 837--846, 1997.

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