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Facial micro-expression refers to split-second muscle changes in the face, indicating that a person is either consciously or unconsciously suppressing their true emotions and even mental health. Therefore, micro-expression recognition attracts increasing research efforts in both fields of psychology and computer vision. Existing research on micro-expression recognition has mainly used hand-crafted...
The process of identifying food items from an image is quite an interesting field with various applications. Since food monitoring plays a leading role in health-related problems, it is becoming more essential in our day-to-day lives. In this paper, an approach has been presented to classify images of food using convolutional neural networks. Unlike the traditional artificial neural networks, convolutional...
Gender recognition from facial images has become one of challenging research problem in computer vision, security, verbal-nonverbal communication and human computer interaction applications nowadays. Because facial images include many information such as gender, facial expressions, age, ethnic origin in computer-aided applications, the success rate of the gender recognition depends on quality of facial...
According to the needs of users, Home Service Robots gradually work outside. As a result, new requirements for the detection and recognition performance of Home Service Robots are put forward. Compared with indoor environment, outdoor environment is more complex, which brings difficulties to detect objects. But extracting features by Histogram of Oriented Gradient (HOG) method can not work well in...
In this paper, we introduce seven emotions and positive and negative emotion recognition methods using facial images and the development of apps based on the method. In previous researches, they used the deep-learning technology to generate models with emotion-based facial expressions to recognized emotions. There are existing apps that express six emotions, but not seven emotions and positive and...
This paper focuses on real=time image recognition in video sequences A novel algorithm designed to be used specifically for finger spelling alphabet is introduced along with relevant qualitative comparison to current state of the art. The proposed concept introduces a new image feature selection technique used in comparation process, which significantly improves the recognition of finger spelling...
Similarity rank lists provide a method for learning generalization of classifiers from examples. Here, we apply it to invariant object recognition and demonstrate that it performs better than other approaches on view and illumination invariant recognition. Recognition from a single view reaches 87% success rate. To study its real world capabilities we introduce subsqare rank matching that works on...
Recent work in the recognition of naturalistic expressions, which is also known as spontaneous facial expressions recognition, has attracted researchers' attention due to its importance in different behavioural and clinical applications. The main design challenges in the area of emotion computing for automatic recognition of spontaneous facial expression are the face pose, capture distance, illumination...
Oil refinery industry is using large amount of radiographic films of weld defects, requiring human work by technicians to interpretation. This paper presents a method and automated system for determination of weld defect from radiographic films by using the image processing technique. The hardware and software system rapidly and automatically convert the radiographic films into digital images, then...
Understanding what a person is experiencing from her frame of reference is essential in our everyday life. For this reason, one can think that machines with this type of ability would interact better with people. However, there are no current systems capable of understanding in detail peoples emotional states. Previous research on computer vision to recognize emotions has mainly focused on analyzing...
Material recognition for real-world outdoor surfaces has become increasingly important for computer vision to support its operation in the wild. Computational surface modeling that underlies material recognition has transitioned from reflectance modeling using in-lab controlled radiometric measurements to image-based representations based on internet-mined images of materials captured in the scene...
This paper combines three contributions to establish a new state-of-the-art in dynamic scene recognition. First, we present a novel ConvNet architecture based on temporal residual units that is fully convolutional in spacetime. Our model augments spatial ResNets with convolutions across time to hierarchically add temporal residuals as the depth of the network increases. Second, existing approaches...
This paper introduces an approach to recognize face from 3D space on 2D image using fuzzy vector manifolds and nearest distance. We employ fuzzy vector to help the system minimize negative effect coming from noise and image degradation. On the training set, crisp vector representation of images will be transformed to its fuzzy vector representation using a specific triangle fuzzification method. Then,...
Multiple view data with different feature representations have widely arisen in various practical applications. Due to the information diversity, fusing multiview features is very valuable for classification purpose. In this paper, we propose a new multifeature fusion method called fractional-order discriminative multiview correlation projection (FDMCP), which is based on fractional-order scatter...
Palm vein recognition is a new biometric identification technology. The horizontal rotation, translation, tilting and loss of local vein information of palm vein image greatly affect recognition rate. To solve the above problems, this paper respectively extract four kinds of local invariant feature, Scale Invariant Feature Transform(SIFT), Affine-SIFT(ASIFT), Harris-Laplace and Maximally Stable Extremal...
Recognizing people's emotions from their frame of reference is very important in our everyday life. This capacity helps us to perceive or predict the subsequent actions of people, interact effectively with them and to be sympathetic and sensitive toward them. Hence, one should expect that a machine needs to have a similar capability of understanding people's feelings in order to correctly interact...
Mobile augmented reality (MAR) is a newly-emerging technology which covers the real scene with virtual information by utilizing the mobile terminal and thus enables users to have a better understanding for and interaction with the real environment. The article makes a research on the application of MAR technology in the smart exhibition hall, expounds the technological principles and key technologies...
In this paper, a novel supervised feature extraction method called Sub-pattern based Maximum Margin Criterion (SpMMC) is developed for face Recognition. Unlike Maximum Margin Criterion (MMC) method which directly extracts the global features from the whole face image, the proposed SpMMC method separately extracts the local features from the sub-images partitioned from the original face image. Moreover,...
A facial expression is exhibited by the movement of muscles underneath the face skin. Automatic Facial Expression Recognition comprises of three main phases: Feature Extraction, Feature Selection and Expression Classification. Facial Expression Recognition (FER) has a very important role in computer vision, human machine interaction and modern gaming. The objective of this research work is to explore...
Sparse representation based classification (SRC) has been introduced as a new algorithm for face recognition classification instead of the classical gradient-based algorithms. However, there are some limitations that influence the robustness properties in SRC. One of the most effective parameters that impacts the SRC performance is the directory of training samples. It should contain enough samples...
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