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Articles 1 - 6 of 6
Full-Text Articles in Physical Sciences and Mathematics
Action Recognition Based On A Bag Of 3d Points, Wanqing Li, Zhenyu Zhang, Zicheng Liu
Action Recognition Based On A Bag Of 3d Points, Wanqing Li, Zhenyu Zhang, Zicheng Liu
Faculty of Informatics - Papers (Archive)
This paper presents a method to recognize human actions from sequences of depth maps. Specifically, we employ an action graph to model explicitly the dynamics of the actions and a bag of 3D points to characterize a set of salient postures that correspond to the nodes in the action graph. In addition, we propose a simple, but effective projection based sampling scheme to sample the bag of 3D points from the depth maps. Experimental results have shown that over 90% recognition accuracy were achieved by sampling only about 1% 3D points from the depth maps. Compared to the 2D silhouette …
Finding Distinctive Facial Areas For Face Recognition, Ce Zhan, Wanqing Li, Philip O. Ogunbona
Finding Distinctive Facial Areas For Face Recognition, Ce Zhan, Wanqing Li, Philip O. Ogunbona
Faculty of Informatics - Papers (Archive)
One of the key issues for local appearance based face recognition methods is that how to find the most discriminative facial areas. Most of the existing methods take the assumption that anatomical facial components, such as the eyes, nose, and mouth, are the most useful areas for recognition. Other more elaborate methods locate the most salient parts within the face according to a pre-specified criterion. In this paper, a novel method is proposed to identify the discriminative facial areas for face recognition. Unlike the existing methods that only analyze the given face, the proposed method identifies the distinctive areas of …
Dimensionality Reduction Using Compressed Sensing And Its Application To A Large-Scale Visual Recognition Task, Son Lam Phung, Fok Hing Chi Tivive, Abdesselam Bouzerdoum, Jie Yang
Dimensionality Reduction Using Compressed Sensing And Its Application To A Large-Scale Visual Recognition Task, Son Lam Phung, Fok Hing Chi Tivive, Abdesselam Bouzerdoum, Jie Yang
Faculty of Informatics - Papers (Archive)
This paper presents a novel algorithm for the dimensionality reduction which employs compressed sensing (CS) to improve the generalization capability of a classifier, especially for large-scale data. Compared to traditional dimensionality reduction methods, the proposed algorithm makes no use of the problem-dependent parameters, nor does it require additional computation for the eigenvalue decomposition like PCA or LDA. Mathematically, the derived algorithm regards the input features as the dictionary in CS, and selects the features that minimize the residual output error iteratively, thus the resulting features have a direct correspondence to the performance requirements of the given problem. Furthermore, the proposed …
Feature Selection For Facial Expression Recognition, Abdesselam Bouzerdoum, Son Lam Phung, Fok Hing Chi Tivive, Peiyao Li
Feature Selection For Facial Expression Recognition, Abdesselam Bouzerdoum, Son Lam Phung, Fok Hing Chi Tivive, Peiyao Li
Faculty of Informatics - Papers (Archive)
In daily interactions, humans convey their emotions through facial expression and other means. There are several facial expressions that reflect distinctive psychological activities such as happiness, surprise or anger. Accurate recognition of these activities via facial image analysis will play a vital role in natural human-computer interfaces, robotics and mimetic games. This paper focuses on the extraction and selection of salient features for facial expression recognition. We introduce a cascade of fixed filters and trainable non-linear 2-D filters, which are based on the biological mechanism of shunting inhibition. The fixed filters are used to extract primitive features, whereas the adaptive …
Adaptive Hierarchical Architecture For Visual Recognition, Fok Hing Chi Tivive, Abdesselam Bouzerdoum, Son Lam Phung, Khan M. Iftekharuddin
Adaptive Hierarchical Architecture For Visual Recognition, Fok Hing Chi Tivive, Abdesselam Bouzerdoum, Son Lam Phung, Khan M. Iftekharuddin
Faculty of Informatics - Papers (Archive)
We propose a new hierarchical architecture for visual pattern classification. The new architecture consists of a set of fixed, directional filters and a set of adaptive filters arranged in a cascade structure. The fixed filters are used to extract primitive features such as orientations and edges that are present in a wide range of objects, whereas the adaptive filters can be trained to find complex features that are specific to a given object. Both types of filters are based on the biological mechanism of shunting inhibition. The proposed architecture is applied to two problems: pedestrian detection and car detection. Evaluation …
Automatic Recognition Of Smiling And Neutral Facial Expressions, Peiyao Li, S L. Phung, Abdesselam Bouzerdoum, Fok Hing Chi Tivive
Automatic Recognition Of Smiling And Neutral Facial Expressions, Peiyao Li, S L. Phung, Abdesselam Bouzerdoum, Fok Hing Chi Tivive
Faculty of Informatics - Papers (Archive)
Facial expression is one way humans convey their emotional states. Accurate recognition of facial expressions via image analysis plays a vital role in perceptual human computer interaction, robotics and online games. This paper focuses on recognising the smiling from the neutral facial expression. We propose a face alignment method to address the localisation error in existing face detection methods. In this paper, smiling and neutral facial expression are differentiated using a novel neural architecture that combines fixed and adaptive non-linear 2-D filters. The fixed filters are used to extract primitive features, whereas the adaptive filters are trained to extract more …