61 research outputs found
Artificial Vision Algorithms for Socially Assistive Robot Applications: A Review of the Literature
Today, computer vision algorithms are very important for different fields and applications, such as closed-circuit television security, health status monitoring, and recognizing a specific person or object and robotics. Regarding this topic, the present paper deals with a recent review of the literature on computer vision algorithms (recognition and tracking of faces, bodies, and objects) oriented towards socially assistive robot applications. The performance, frames per second (FPS) processing speed, and hardware implemented to run the algorithms are highlighted by comparing the available solutions. Moreover, this paper provides general information for researchers interested in knowing which vision algorithms are available, enabling them to select the one that is most suitable to include in their robotic system applicationsBeca Conacyt Doctorado No de CVU: 64683
Dynamic Facial Expression Generation on Hilbert Hypersphere with Conditional Wasserstein Generative Adversarial Nets
In this work, we propose a novel approach for generating videos of the six
basic facial expressions given a neutral face image. We propose to exploit the
face geometry by modeling the facial landmarks motion as curves encoded as
points on a hypersphere. By proposing a conditional version of manifold-valued
Wasserstein generative adversarial network (GAN) for motion generation on the
hypersphere, we learn the distribution of facial expression dynamics of
different classes, from which we synthesize new facial expression motions. The
resulting motions can be transformed to sequences of landmarks and then to
images sequences by editing the texture information using another conditional
Generative Adversarial Network. To the best of our knowledge, this is the first
work that explores manifold-valued representations with GAN to address the
problem of dynamic facial expression generation. We evaluate our proposed
approach both quantitatively and qualitatively on two public datasets;
Oulu-CASIA and MUG Facial Expression. Our experimental results demonstrate the
effectiveness of our approach in generating realistic videos with continuous
motion, realistic appearance and identity preservation. We also show the
efficiency of our framework for dynamic facial expressions generation, dynamic
facial expression transfer and data augmentation for training improved emotion
recognition models
Facial emotion expressions in human-robot interaction: A survey
Facial expressions are an ideal means of communicating one's emotions or
intentions to others. This overview will focus on human facial expression
recognition as well as robotic facial expression generation. In case of human
facial expression recognition, both facial expression recognition on predefined
datasets as well as in real time will be covered. For robotic facial expression
generation, hand coded and automated methods i.e., facial expressions of a
robot are generated by moving the features (eyes, mouth) of the robot by hand
coding or automatically using machine learning techniques, will also be
covered. There are already plenty of studies that achieve high accuracy for
emotion expression recognition on predefined datasets, but the accuracy for
facial expression recognition in real time is comparatively lower. In case of
expression generation in robots, while most of the robots are capable of making
basic facial expressions, there are not many studies that enable robots to do
so automatically.Comment: Pre-print version. Accepted in International Journal of Social
Robotic
- …