Intention prediction has become a relevant field of research in Human–Machine and Human–
Robot Interaction. Indeed, any artificial system (co)-operating with and along humans …

Video-based recognition of activities of daily living (ADLs) is being used in ambient assisted
living systems in order to support the independent living of older people. However, current …

Activity detection and classification are very important for autonomous monitoring of humans
for applications, including assistive living, rehabilitation, and surveillance. Wearable sensors …

Understanding social interactions from egocentric views is crucial for many applications,
ranging from assistive robotics to AR/VR. Key to reasoning about interactions is to …

We present EgoHumans, a new multi-view multi-human video benchmark to advance the
state-of-the-art of egocentric human 3D pose estimation and tracking. Existing egocentric …

We focus on the problem of wearer's action recognition in first person aka egocentric videos.
This problem is more challenging than third person activity recognition due to unavailability …

The egocentric action recognition EAR field has recently increased its popularity due to the
affordable and lightweight wearable cameras available nowadays such as GoPro and …

The emergence of new wearable technologies, such as action cameras and smart glasses,
has increased the interest of computer vision scientists in the first person perspective …

The use of wearable cameras makes it possible to record life logging egocentric videos.
Browsing such long unstructured videos is time consuming and tedious. Segmentation into …

Recognizing human activities from videos is a fundamental research problem in computer
vision. Recently, there has been a growing interest in analyzing human behavior from data …