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Face recognition in video surveillance is challenging as there is no control on the quality of the face image captured especially under uncooperative situations with head pose variation, occlusion, and low-quality image. These issues create large discrepancy between probe and gallery images which affects the performance of recognition. To overcome these issues, pose correction is proposed to narrow...
A visually impaired person or a person with visually impaired, daily has difficulties to learn to recognize or differentiate objects when performing any activity, such as walking the streets or being able to recognize dollar bills of different denomination, this makes that the people with this type of disability cannot adapt easily to the society. Usually the visually impaired persons depend on someone...
Attendance is an important part of classroom evaluation. This paper develops a university classroom automatic attendance system by integrating two deep learning algorithms MTCNN face detection and Center-Face face recognition. A large number of experimental results show that: (1) The system can record such three violations of classroom discipline for automatic attendance, that is absence, lateness...
Facial alignment involves finding a set of landmark points on an image with a known semantic meaning. However, this semantic meaning of landmark points is often lost in 2D approaches where landmarks are either moved to visible boundaries or ignored as the pose of the face changes. In order to extract consistent alignment points across large poses, the 3D structure of the face must be considered in...
Conventional studies on human behavior recognition have mainly focused on individual actions, including facial expressions and postures. However, most human behavior involves face-to-face interactions with other humans or objects, such as PCs. The previous work on recognizing face-to-face interaction focused on recognition of each group of humans engaged in conversation in an open space, which is...
Biometrics are beneficial to keep the information of a person secured in our daily life. The various biometrics like face recognition, iris recognition, vein recognition, lips patterns and finger prints have become robust features in research world. Among all difference types of biometrics, Iris Recognition is one of the great importance because it has extraordinary variation in texture. A hypersensitive...
Virtual characters play a central role in populating virtual worlds, whether they act as conduits for human expressions as avatars or are automatically controlled by a machine as agents. In modern game-related scenarios, it is economical to assemble virtual characters from varying sources of appearances and motions. However, doing so may have unintended consequences with respect to how people perceive...
This paper describes a face recognition-based people tracking and re-identification system for RGB-D camera networks. The system tracks people and learns their faces online to keep track of their identities even if they move out from the camera's field of view once. For robust people re-identification, the system exploits the combination of a deep neural network- based face representation and a Bayesian...
The deployment of police super-recognisers (SRs) with exceptional face recognition ability, has transformed the manner in which some forces manage CCTV evidence. In London, SRs make high numbers of sometimes disguised suspect identifications from CCTV. In two experiments measuring immediate and one-week memory of unfamiliar faces in disguise, SRs were more accurate and confident than controls at correctly...
The system proposed in this paper is an innovative biometrie authentication platform for access control applications based face recognition. The vision system is based multisensor fusion combining catadioptric sensor (calibrated with a field of view of 360°) and a Pan Tilt Zoom camera (PTZ). It is able to detect and track moving objects with a high zoom level. The recognition process is based on detection...
To prevent counterfeit face image on face presence system, we can use dual vision camera in face recognition system. Dual vision camera is used to produce detectable face images from two positions of the left lens and the right lens. Image retrieval at the two corners of the left lens and the right lens can produce a merged face image database of left lens face image and right lens face image. The...
This paper presents a novel technique for face recognition based on facial landmarks extracted automatically. Our landmarks are those associated with eyes mouth and nose. With the extracted landmarks, the area triplets and the associated geometric invariance are formed. We opt to use area and triangle confined within the triangle as the invariance. To bypass the perspective constraints, we take the...
The growing interest in recent years for gender recognition from face images is mainly attributable to the wide range of possible applications that can be used for commercial and marketing purposes. It is desirable that such algorithms process high resolution video frames acquired by using surveillance cameras in real-time. To the best of our knowledge, however, there are no studies which analyze...
Information and Communication Technology is always walking in the forefront of human education. Now, it is the stage where human education has to adapt itself to the developing technologies. In 2016, the Natural Science Foundation suggested that people need to use the human-technology to improve and extend the human learning. This paper provides the concept of Software Defined Class (SDC), where the...
Affective facial expression is a key feature of nonverbal behaviour and is considered as a symptom of an internal emotional state. Emotion recognition plays an important role in social communication: human-to-human and also for human-to-robot. Taking this as inspiration, this work aims at the development of a framework able to recognise human emotions through facial expression for human-robot interaction...
Recent advances have enabled oracle classifiers that can classify across many classes and input distributions with high accuracy without retraining. However, these classifiers are relatively heavyweight, so that applying them to classify video is costly. We show that day-to-day video exhibits highly skewed class distributions over the short term, and that these distributions can be classified by much...
In this work we present three methods to improve a deep convolutional neural network approach to near-infrared heterogeneous face recognition. We first present a method to distill extra information from a pre-trained visible face network through the output logits of the network. Next, we put forth an altered contrastive loss function that uses the ℓ1 norm instead of the ℓ2 norm as a distance metric...
While face recognition algorithms perform under many different unconstrained conditions, predicting this performance is not possible when a new location is introduced. Analyzing the impostor distribution of the videos of the Point-and-Shoot Challenge (PaSC) as well as its relationship to the genuine match distribution, we present a method for predicting the performance of an algorithm using only unlabeled...
Computer vision based technologies have seen widespread adoption over the recent years. This use is not limited to the rapid adoption of facial recognition technology but extends to facial expression recognition, scene recognition and more. These developments raise privacy concerns and call for novel solutions to ensure adequate user awareness, and ideally, control over the resulting collection and...
"STAT (U) ES" is an interactive art that enables a subjective experience of site-specificity using projectionmapping and facial recognition system. This work consists of two parts, a camera part that captures facial images and a projection part where an image of the Buddhist Sculpture is projected on wooden boxes. A viewer is first instructed to read the caption of the work and the facial...
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