I study experimentally a single-shot trust game where players have the opportunity to choose an avatar—a computer-generated face—to represent them. These avatars vary on several dimensions—trustworthiness, dominance, and threat—identified by previous work as influencing perceptions of those who view the faces (Todorov, Said, Engell, & Oosterhof, 2008). I take this previous work and ask whether ...

A recent paper demonstrated that the pattern of firing rates across ∼100 neurons in the anterior medial face patch is closely related to which human face (of 2,000) had been presented to a monkey [Chang L, Tsao DY (2017) Cell 169:1013-1028]. In addition, the firing rates for these neurons can be predicted for a novel human face. Although it is clear from this work that the firing rates of these...

© 2 0 0 3 m a s s a c h u s e t t s i n s t i t u t e o f t e c h n o l o g y, c a m b r i d g e , m a 0 2 1 3 9 u s a — w w w. a i. m i t. e d u m a s s a c h u s e t t s i n s t i t u t e o f t e c h n o l o g y — a r t i f i c i a l i n t e l l i g e n c e l a b o r a t o r y @ MIT Abstract The central challenge in face recognition lies in understanding the role different facial features pla...

For the purpose of face recognition (FR), the new color local texture features, i.e., color local Gabor wavelets (CLGWs) and color local binary pattern (CLBP), are being proposed. The proposed color local texture features are able to exploit the discriminative information derived from spatiochromatic texture patterns of different spectral channels within a certain local face region. This method...

There are many Local texture features each very in way they implement and each of the Algorithm trying improve the performance. An attempt is made in this paper to represent a theoretically very simple and computationally effective approach for face recognition. In our implementation the face image is divided into 3x3 sub-regions from which the features are extracted using the Local Binary Patt...

In this paper we introduce the DCT-mod2 facial feature extraction technique which utilizes polynomial coefficients derived from 2-D DCT coefficients of spatially neighbouring blocks. We evaluate its robustness and performance against three popular feature sets for use in an identity verification system subject to illumination changes. Results on the multi-session VidTIMIT database suggest that ...

Face recognition, means checking for the presence of a face from a database that contains many faces and could be performed using the different features. The face images considered for recognition undergo large variations due to changes in the illumination conditions, viewing direction, facial expression and aging. The face images have similar geometrical features. Hence, it is a challenging ta...

Invariant feature extraction is one of the most difficult problems in machine vision. Human face detection and recognition have recently become an important application area of computer vision. In this paper, a novel illumination, translation, rotation, and scale invariant feature extraction method based on Gabor filtering is introduced. The proposed method is successfully applied to invariant ...

For face recognition, face feature selection is an important step. Better features should result in better performance. This paper describes a robust face recognition algorithm using multiple face region features selected by the AdaBoost algorithm. In conventional face recognition algorithms, the face region is dealt with as a whole. In this paper we show that dividing a face into a number of s...

Article history: Received 25 October 2015 Received in revised form 28 March 2017 Accepted 13 May 2017 Available online 31 May 2017 In this paper, we propose a robust local descriptor for face recognition. It consists of two components, one based on a shearlet-decomposition and the other on local binary pattern (LBP). Shearlets can completely analyze the singular structures of piecewise smooth i...