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.
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...
This study presents an age and gender estimation system that considers ethnic difference in face images using a Convolutional Neural Network(CNN) and Support Vector Machine(SVM). Most age and gender estimation systems using face images are trained on ethnicity-biased databases. Therefore, these systems show limited performance on face images of ethnic groups occupying a small proportion of the training...
We are developing an appearance-based proficiency evaluation system for individual fundamental football skills. As a basic stage of the research, we propose a method to discriminate between beginners and experts based on features of the inside-kick motion, which is a fundamental skill in football. In addition, we propose a method for scoring the inside-kick motion. To provide ground truth, a football...
An EMG (electromyogram)-angle neural network was built to estimate elbow movement in a lifting task from sEMG signals in this study. The movement conditions vary with 6 different weights and no load. Subsequently the predicted angle could be utilized as the control signal of a 2DOF powered exoskeleton. Sixteen-channel EMG raw data sets were acquired from two commercial wearable MYO gesture armbands...
Autonomous positioning of small objects to create heterogeneous structures has great potential to advance the current micromanipulation procedures. To achieve autonomous micromanipulation, it is required to recognize the manipulation events. In this work, different classification algorithms including five common supervised learning methods are assessed for identifying states of manipulation. The classifiers...
This paper presents a cell recognition method aiming at guiding the implementation more simply and effectively for injecting multiple cells using biological cell injection systems. The cells are randomly placed in the field of view of a microscope. In particular, the method is proposed to guide the cell grasping device through computer vision to grasp multiple cells in a field of image region without...
Robotic graspable object recognition is a crucial ingredient in many exciting autonomous manipulation applications. However, identifying complex image features from limited data remains largely unsolved. In this paper, we leverage the advantages of two kinds of feature representation approaches, kernel descriptors and deep neural networks, to present a novel hierarchical feature learning framework...
We propose a new task of unsupervised action detection by action matching. Given two long videos, the objective is to temporally detect all pairs of matching video segments. A pair of video segments are matched if they share the same human action. The task is category independent—it does not matter what action is being performed—and no supervision is used to discover such video segments. Unsupervised...
Previous studies of robots used in learning environments suggest that the interaction between learner and robot is able to enhance the learning procedure towards a better engagement of the learner. Moreover, intelligent robots can also adapt their behavior during a learning process according to certain criteria resulting in increasing cognitive learning gains. Motivated by these results, we propose...
Error-Related Potentials (ErrPs) have been used lately in order to improve several existing Brain-Computer Interface (BCI) applications. In our study we investigate the contribution of ErrPs in a Steady State Visual Evoked Potential (SSVEP) based BCI. An extensive study is presented in order to discover the limitations of the proposed scheme. Using Common Spatial Patterns and Random Forests we manage...
In this paper the authors introduce a method focusing on the robustness improvement of the landmark tracking system for mobile robot operation in natural environments. We extract feature points from the data obtained by a stereo vision system with CenSurE (Center Surround Extremas for Realtime Feature Detection and Matching) used as a detector, and FREAK (Fast Retina Keypoint) as a descriptor. RANSAC...
This paper proposes a method of vision based pose estimation of randomly piled objects. It is necessary to estimate precise rotation angle of picking objects. However, it is non-trivial task because an object placed in every position makes distorted image far from right position image. We propose a precise pose estimation method of bin picking objects. The landmark feature of a picking object is extracted...
Scene flow is a key function of stereo-based environment perception system for mobile robotics and autonomous vehicle. Due to the heavy computing requirement and the limited computing resource, parallelized and embedded algorithms become quite important for the application of the mobile robotics. This paper develops a cross-platform embedded scene flow algorithm by using a coarse-grained software...
We summarize a method to generate a synthetic learning set for object pose estimation in robotic manipulation tasks. Exploiting modern computer graphics techniques, our synthetic learning set satisfies the requirements both in quantitative diversity and qualitative precision. We report the partial results of initial experiments and discuss some future research directions.
Evaluation of a person's posture while exercising is important in physical therapy. During a therapy session, a physical therapist or a monitoring system must assure that the person is performing an exercise correctly to achieve the desired therapeutic effect. In this work, we introduce a system called PostureCheck for exercise assessment in physical therapy. PostureCheck assesses the posture of a...
Object detection and pose estimation is a fundamental functionality among robotic perception for manipulation. Applying robots to diverse tasks requires a robust perception skill. In this manuscript, we introduce an overview of our object recognition and pose estimation process and its our initial results. Our approach follows the previous approaches using local feature extraction and match. As a...
In this paper, a fully-autonomous quadrotor aerial robot for solving the different missions proposed in the 2016 International Micro Air Vehicle (IMAV) Indoor Competition is presented. The missions proposed in the IMAV 2016 competition involve the execution of high-level missions such as entering and exiting a building, exploring an unknown indoor environment, recognizing and interacting with objects,...
A common problem in Brain-Machine Interface (BMI) is the variations in neural signals over time, leading to significant decrease in decoding performance if the decoder is not re-trained. However, frequent re-training is not practical in real use case. In our work, we found that a temporally more robust system may be achieved through the use of wavelet transform in feature extraction. We used wavelet...
This paper presents a fire heading estimation for solving the autonomous navigation problem of a firefighting robot in smoke-filled indoor fire environment. In smoke-filled fire environments, firefighters and firefighting robots experience difficulty maintaining direction while finding the fire source. To solve this, the statistical texture features in thermal images were analyzed and fused by using...
Weed scouting is an important part of modern integrated weed management but can be time consuming and sparse when performed manually. Automated weed scouting and weed destruction has typically been performed using classification systems able to classify a set group of species known a priori. This greatly limits deployability as classification systems must be retrained for any field with a different...
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.