Related papers: IJCB 2022 Mobile Behavioral Biometrics Competition…
Twitter bots are automatic programs operated by malicious actors to manipulate public opinion and spread misinformation. Research efforts have been made to automatically identify bots based on texts and networks on social media. Existing…
Implicit authentication (IA) is gaining popularity over recent years due to its use of user behavior as the main input, relieving users from explicit actions such as remembering and entering passwords. However, such convenience comes with a…
Mobile devices have become a popular tool for ubiquitous learning in recent years. Multiple mobile users can be connected via ad hoc networks for the purpose of learning. In this context, due to limited battery capacity, energy efficiency…
Mobile sensing plays a crucial role in generating digital traces to understand human daily lives. However, studying behaviours like mood or sleep quality in smartphone users requires carefully designed mobile sensing strategies such as…
In view of the fact that biological characteristics have excellent independent distinguishing characteristics,biometric identification technology involves almost all the relevant areas of human distinction. Fingerprints, iris, face,…
The embedded sensors in widely used smartphones and other wearable devices make the data of human activities more accessible. However, recognizing different human activities from the wearable sensor data remains a challenging research…
Biosignal interfaces, using sensors in, on, or around the body, promise to enhance wearables interaction and improve device accessibility for people with motor disabilities. However, biosignals are multi-modal, multi-dimensional, and noisy,…
This work presents a deep reinforcement learning framework for interactive navigation in a crowded place. Our proposed approach, Learning to Balance (L2B) framework enables mobile robot agents to steer safely towards their destinations by…
The massive availability of cameras results in a wide variability of imaging conditions, producing large intra-class variations and a significant performance drop if heterogeneous images are compared for person recognition. However, as…
This study uses multisensory data (i.e., color and depth) to recognize human actions in the context of multimodal human-robot interaction. Here we employed the iCub robot to observe the predefined actions of the human partners by using four…
Biometrics are widely used for authentication in consumer devices and business settings as they provide sufficiently strong security, instant verification and convenience for users. However, biometrics are hard to keep secret, stolen…
In Human-Computer Interaction (HCI) and Ubiquitous Computing, the objective of optimizing device interactions and personalizing user experiences has placed a new emphasis on accurately evaluating cognitive readiness using wearable devices.…
In this work, we study a novel problem which focuses on person identification while performing daily activities. Learning biometric features from RGB videos is challenging due to spatio-temporal complexity and presence of appearance biases…
Efficient and low-latency wireless connectivity between the base station (BS) and a sparse set of sporadically active devices from a massive number of devices is crucial for random access in emerging massive machine-type communications…
This paper discusses some topics related to the latest trends in the field of evolutionary approaches to iris recognition. It presents the results of an exploratory experimental simulation whose goal was to analyze the possibility of…
We present Whole-Body Mobile Manipulation Interface (HoMMI), a data collection and policy learning framework that learns whole-body mobile manipulation directly from robot-free human demonstrations. We augment UMI interfaces with egocentric…
We propose an enhanced version of the Authentication with Built-in Camera (ABC) protocol by employing a deep learning solution based on built-in motion sensors. The standard ABC protocol identifies mobile devices based on the photo-response…
With the advent of cheap computing through five decades of continued miniaturization following Moores Law, wearable devices are becoming increasingly popular. These wearable devices are typically interconnected using wireless body area…
We propose Breath to Pair (B2P), a protocol for pairing and shared-key generation for wearable devices that leverages the wearer's respiration activity to ensure that the devices are part of the same body-area network. We assume that the…
In recent years, there has been a shift of interest towards the field of biometric authentication, which proves the identity of the user using their biological characteristics. We explore a novel biometric based on the electrical activity…