Search results for " image processing."
showing 10 items of 2265 documents
Automatic landmark detection and 3D Face data extraction
2017
Abstract This paper contributes to 3D facial synthesis by presenting a novel method for parameterization using Landmark Point detection. The approach presented aims at improving facial recognition even in varying facial expressions, and missing data in 3D facial models. As such, the prime objective was to develop an automatically embedded process that can detect any frontal face in 3D face recognition systems, with face segmentation and surface curvature information. Using the hybrid interpolation method, experiments on facial landmarks were performed on 4950 images from Face Recognition Grand Challenge database (FRGC). Distinctive facial landmarks from the nose–tips, Limits mouth and two e…
Remote heart rate variability for emotional state monitoring
2018
International audience; Several researches have been conducted to recognize emotions using various modalities such as facial expressions , gestures, speech or physiological signals. Among all these modalities, physiological signals are especially interesting because they are mainly controlled by the autonomic nervous system. It has been shown for example that there is an undeniable relationship between emotional state and Heart Rate Variability (HRV). In this paper, we present a methodology to monitor emotional state from physiological signals acquired remotely. The method is based on a remote photoplethysmography (rPPG) algorithm that estimates remote Heart Rate Variability (rHRV) using a …
Video-based Pain Level Assessment: Feature Selection and Inter-Subject Variability Modeling
2018
Automatic pain level assessment, based on video features, may provide clinically-relevant, objective measures of pain intensity. In various clinical contexts accurate pain level estimation by health care personnel is challenging. This problem is compounded by considerable inter- and intra-individual variability of both perceived pain levels and of the associated facial expressions, especially at low pain levels. Thus, providing objective video-based indices for pain level assessment is a rather computationally challenging problem. In the present work both geometric and color-based features were extracted. The most informative features were identified with lasso regression, and subject varia…
Towards Psychologically based Personalised Modelling of Emotions Using Associative Classifiers
2016
Learning environments, among other user-centred applications, are excellent candidates to trial Computational Emotions and their algorithms to enhance user experience and to expand the system usability. However, this was not feasible because of the paucity in affordable consumer technologies that support the requirements of systems with advanced cognitive capabilities. Microsoft Kinect provides an accessible and affordable technology that can enable cognitive features such as facial expressions extraction and emotions detection. However, it comes with its own additional challenges, such as the limited number of extracted Animation Units (AUs). This paper presents a new approach that attempt…
Effective feature descriptor-based new framework for off-line text-independent writer identification
2018
Feature engineering is a key factor of machine learning applications. It is a fundamental process in writer identification of handwriting, which is an active and challenging field of research for many years. We propose a conceptually computationally efficient, yet simple and fast local descriptor referred to as Block Wise Local Binary Count (BW-LBC) for offline text-independent writer identification of handwritten documents. Proposed BW-LBC operator, which characterizes the writing style of each writer, is applied to a set of connected components extracted and cropped from scanned handwriting samples (documents or set of words/text lines) where each labeled component is seen as a texture im…
CitySearcher: A City Search Engine For Interests
2017
We introduce CitySearcher, a vertical search engine that searches for cities when queried for an interest. Generally in search engines, utilization of semantics between words is favorable for performance improvement. Even though ambiguous query words have multiple semantic meanings, search engines can return diversified results to satisfy different users' information needs. But for CitySearcher, mismatched semantic relationships can lead to extremely unsatisfactory results. For example, the city Sale would incorrectly rank high for the interest shopping because of semantic interpretations of the words. Thus in our system, the main challenge is to eliminate the mismatched semantic relationsh…
Combining feature extraction and expansion to improve classification based similarity learning
2017
Abstract Metric learning has been shown to outperform standard classification based similarity learning in a number of different contexts. In this paper, we show that the performance of classification similarity learning strongly depends on the data format used to learn the model. We then present an Enriched Classification Similarity Learning method that follows a hybrid approach that combines both feature extraction and feature expansion. In particular, we propose a data transformation and the use of a set of standard distances to supplement the information provided by the feature vectors of the training samples. The method is compared to state-of-the-art feature extraction and metric lear…
Fair Planning and Affordability Housing in Urban Policy. The Case of Syracuse (Italy)
2016
Equalization can be implemented in the planning process by means of several tools. The Syracuse’s Master Plan has used “urban negotiation” to obtain land for facilities and public infrastructure in different urban areas basing on the rule of the transfer of a portion of land in return for the building permission for the remaining part of each property to be developed. The Master Plan also aimed at providing social housing because the economic crisis has amplified the gap between housing market prices and household income. This study proposes an equalization and compensation model to support the urban negotiation for providing the indexes of a fair and convenient development of several inter…
Performance of Fine-Tuning Convolutional Neural Networks for HEp-2 Image Classification
2020
The search for anti-nucleus antibodies (ANA) represents a fundamental step in the diagnosis of autoimmune diseases. The test considered the gold standard for ANA research is indirect immunofluorescence (IIF). The best substrate for ANA detection is provided by Human Epithelial type 2 (HEp-2) cells. The first phase of HEp-2 type image analysis involves the classification of fluorescence intensity in the positive/negative classes. However, the analysis of IIF images is difficult to perform and particularly dependent on the experience of the immunologist. For this reason, the interest of the scientific community in finding relevant technological solutions to the problem has been high. Deep lea…
Deep Convolutional Neural Networks for Fire Detection in Images
2017
Detecting fire in images using image processing and computer vision techniques has gained a lot of attention from researchers during the past few years. Indeed, with sufficient accuracy, such systems may outperform traditional fire detection equipment. One of the most promising techniques used in this area is Convolutional Neural Networks (CNNs). However, the previous research on fire detection with CNNs has only been evaluated on balanced datasets, which may give misleading information on real-world performance, where fire is a rare event. Actually, as demonstrated in this paper, it turns out that a traditional CNN performs relatively poorly when evaluated on the more realistically balance…