Recognition of facial expressions using Gabor wavelets and learning vector quantization

Bashyal, Shristy; Venayagamoorthy, G.K.

doi:10.1016/j.engappai.2007.11.010

Cited by 193 publications

(75 citation statements)

References 7 publications

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“…Geometry based techniques include Haar-like feature extraction, LBP, and Gabor wavelets. [4] proposed recognition of facial expressions using Gabor wavelets and Learning Vector Quantization (LVQ). This method was used to recognize seven different facial expressions from still pictures of the human face.…”

Section: Emotion Recognitionmentioning

confidence: 99%

Effective recognition of facial micro-expressions with video motion magnification

Wang

See

et al. 2016

Multimed Tools Appl

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Section: Emotion Recognitionmentioning

confidence: 99%

Effective recognition of facial micro-expressions with video motion magnification

Wang

See

et al. 2016

Multimed Tools Appl

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“…However a text independent system can be suitably modelled as a collection of discrete frame templates with no time sequence information, or a VQ model. Since LMS is under study, the baseline model is fixed throughout, and VQ is proven in face and speech recognition [30,31,32,33] this paper integrates LMS with a baseline or conventionall VQ model. The ease of computation makes VQ a suitable framework to evaluate long-range LMS dynamics against conventiona VQ training models with static and dynamic delta features in person identification.…”

Section: Modelling the Video Temporal Dynamics For Person Identificationmentioning

confidence: 99%

Person Identification From Text Independent Lip Movement Using the Longest Matching Segment Method

2017

IJCSI

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The use of lipreading as a standalone modality for biometric classification continues to gain ground but is still presented with several real world challenges. The paper presents a novel form of video temporal modelling using the Longest Matching Segment (LMS) method on a given baseline training model. LMS uses a Vector Quantization (VQ) model to encode full training video dynamics by mapping it to a frame sequence of maximum likelihood codewords. The model is applied to person identification from text independent lip movement on segmented test sets of the CMU-PIE, VidTIMIT and XM2VTS talking datasets and identification is based on the class with the longest matching segment. The results show that LMS improves the conventional VQ models especially when combined with dynamic delta features. Combined with magnitude 2D-FFT (Mag-2D-FFT) features, the system delivers comparable accuracies to full face recognition.

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“…Recognition of facial expressions using Gabor wavelets and learning vector quantization: It is observed that LVQ based feature classification technique proposed in this study performs better in recognizing fear expressions than multilayer perceptron (MLP) based classification technique. [14][15].…”

Section: Related Work Various Face Recognition Techniques and Their Rmentioning

confidence: 99%

Multi-scale and Multi-orientation Face Recognition using Voting based Extreme Learning Machine

Shadi¹,

Khandelwal²

2016

IJCA

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In our daily life human can remember many faces and can recognize them irrespective of illumination, aging, obstructions, variation in views. Most of researchers have worked on the problem of face recognition to develop an automatic face recognition system with capabilities to recognize faces as human beings can do. However, in unconstrained situations where a face may be captured in outdoor environmental conditions, while under changing illumination and pose variations Face Recog-nition Techniques fails to work. Here, a new face recognition method is implemented based on Gabor filter and Voting based extreme learning machine, it presents an effective algorithm to pose invariant face recognition called as Multiscale and Multi-orientation face classification using voting based extreme learning machine. In proposed approach, facial features are extracted by applying set of Gabor filters and Local directional Pattern (LDP), then histogram pattern of result is obtained which is subjected to generate distinctive feature vectors and further classified using V-ELM classifier.The application area of Wireless sensor network(WSN) in real time environment are unreliable and inaccessible , leads to degradation of network performance. The major issues of WSN are QoS ,power and it is impossible to access the WSN to change its power capacity. Long -hops transmission i.e. high range communication which provides the QoS with more energy consumption leads to reduction in network lifetime. The paper concentrates on adjustment of power , range and bit rates to attain adaptive topology control(ATC) at physical layer to maintain equivalent QoS. The simulation are carries out by using MIXIM 2.3 framework Omnet++ 4.6.The comparison of QoS for non-ATC and ATC is presented and an improvement of 29 percentage was resulted.

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Recognition of facial expressions using Gabor wavelets and learning vector quantization

Cited by 193 publications

References 7 publications

Effective recognition of facial micro-expressions with video motion magnification

Effective recognition of facial micro-expressions with video motion magnification

Person Identification From Text Independent Lip Movement Using the Longest Matching Segment Method

Multi-scale and Multi-orientation Face Recognition using Voting based Extreme Learning Machine

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