The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper tackles the problem of reconstructing 3D human poses from 2D landmarks, which is still an ill-posed problem. A widely-used approach is active shape model (ASM) which considers an unknown 3D shape as a linear combination of predefined basis shapes. The existing methods often resolve an optimization problem to reckon the weights and viewpoints of basis shapes, but they could fall into a locally-optimal...
Hand gesture has been used in different applications and implemented on different platforms. Hence, a real-time and robust approach with high recognition accuracy is important in smart devices. This paper describes a novel method of hand gesture recognition using Principle Component Analysis (PCA) implemented in Android phone. Area features are adopted to do the gesture recognition. It solves these...
Identification of colorants of artworks is of paramount importance in the context of museums and art galleries. We present a technique to discriminate the fiber dyes into natural or synthetic class using principal component analysis (PCA). Spectral imaging is used to measure the reflectance spectra of a variety of dyed wools in visible to near infrared (Vis/NIR): 400–1000 nm and short wave infrared...
Large amounts of visual data are gathered from various surveillance systems across different places and times, and have to be processed in order to infer the current state of the world. One of the common problems in surveillance scenarios is person re-identification, the task of associating a person across different cameras. On the other hand, these scenarios raise privacy concerns, which lead to...
Regularized local linear model has been shown to be an effective approach for reflectance estimation. This approach estimates the reflectance of each test point by the linear combination of only its neighbors. The choice of neighbors is of crucial importance to achieve high estimation accuracy. We propose a principal components analysis based neighborhood selection method to reduce model bias. The...
Sensor pattern noise is an inherent fingerprint of imaging devices, which has been widely used for source camera identification, image classification, and forgery detection. In a previous work, we proposed a feature extraction method based on the principal component analysis denoising concept, which can enhance the performance of conventional SPN extraction methods. However, this method is vulnerable,...
The tracking of moving points in image sequences requires unique features that can be easily distinguished. However, traditional feature descriptors are of high dimension, leading to larger storage requirement and slower computation. In this paper, Principal Component Analysis (PCA) is applied to the 64-Dimension (D) Speeded Up Robust Features (SURF) descriptor to reduce the descriptor dimensionality...
Human re-identification remains one of the fundamental, difficult problems in video surveillance and analysis. Current metric learning algorithms mainly focus on finding an optimized vector space such that observations of the same person in this space have a smaller distance than observations of two different people. In this paper, we propose a novel metric learning approach to the human reidentification...
Due to availability of reliable and low cost devices, range maps (depth maps) are extensively used in many applications. Recent advances in human-computer interaction enabled us to interact with computers in intuitive and friendly way. In this paper, we propose a novel approach for recognizing static hand gestures using depth information captured from Photon Mixing Device (PMD) cameras. We segment...
We study the use of domain adaptation and transfer learning techniques as part of a framework for adaptive object detection. Unlike recent applications of domain adaptation work in computer vision, which generally focus on image classification, we explore the problem of extreme class imbalance present when performing domain adaptation for object detection. The main difficulty caused by this imbalance...
Rendering realistic lips movements in avatar with camera captured human's facial features is desirable in many applications, e.g. telepresence, video gaming, social networking, etc. We have proposed to use Gaussian Mixture Model (GMM) to generate lips trajectory and successfully tested in speech-to-lips conversion experiments, where only audio signal (speech) is used as input. In this paper real-time...
In this paper, a novel 3-D action recognition method based on sparse representation is presented. Silhouette images from multiple cameras are combined to obtain motion history volumes (MHVs). Cylindrical Fourier transform of MHVs is used as action descriptors. We assume that a test sample has a sparse representation in the space of training samples. We cast the action classification problem as an...
A novel algorithm for view-invariant human action recognition is presented. This approach is based on Two-Dimensional Principal Component Analysis (2DPCA) applied directly on the Motion Energy Image (MEI) or the Motion History Image (MHI) in both the spatial domain and the transform domain. This method reduces the computational complexity by a factor of at least 66, achieving the highest recognition...
We propose a no-reference algorithm to assess the comfort associated with viewing stereo images and videos. The proposed measure of 3D quality of experience is shown to correlate well with human perception of quality on a publicly available dataset of 3D images/videos and human subjective scores. The proposed measure extracts statistical features from disparity and disparity gradient maps as well...
This paper presents a real-time face recognition system. The system uses a stereo camera to locate, track, and recognize a person's face. Our algorithm improves state-of-the-art monocular 2D object recognition techniques by additionally considering the facial 3D surface, which is relatively stable under different lighting conditions. First, faces are detected and their surfaces are reconstructed from...
Hand pose recognition has been a problem of great interest to the Computer Vision and Human Computer Interaction community for many years and the current solutions either require additional accessories at the user end or enormous computation time. These limitations arise mainly due to the high dexterity of human hand and occlusions created in the limited view of the camera. This work utilizes the...
As a temporal classification problem, visual-based human actions recognition is an important component for some potential applications. In this paper, we combine Fuzzy Principle Component Analysis(Fuzzy PCA) and hidden Conditional Random Fields(HCRFs) to achieve a viewpoint insensitive human action recognition. Fuzzy PCA is used to reduce the dimension of the silhouette image features to obtain the...
This paper presents a simple yet effective approach for classification of human postures by using a time-of-flight camera. We investigate and adopt linear projection techniques such as Locality Preserving Projections (LPP), Linear Discriminant Analysis (LDA) and Principal Component Analysis (PCA), which are more widespread in face recognition and other pattern recognition tasks. We analyze the relations...
This paper presents a multi-view approach to performance evaluation of soccer players by the analysis of the posture evolution. Some body-appearance features have been extracted and the most significant ones have been used to model the activity of the players involved in play. Continuous Hidden Markov Models have been used to model the temporal evolution of the body features in a multiple view decision...
Faces captured by surveillance cameras are often of very low resolution. This significantly deteriorates face recognition performance. Super-resolution techniques have been proposed in the past to mitigate this. This paper proposes the novel use of a Locality Preserving Projections (LPP) algorithm called Direct Locality Preserving Projections (DLPP) for super resolution of facial images, or ldquoface...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.