Visual lifelogging consists of acquiring images that capture the daily experiences of the user
by wearing a camera over a long period of time. The pictures taken offer considerable …

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

We present a video summarization approach for egocentric or “wearable” camera data.
Given hours of video, the proposed method produces a compact storyboard summary of the …

We present a video summarization approach that discovers the story of an egocentric video.
Given a long input video, our method selects a short chain of video subshots depicting the …

This paper presents a method for the detection and recognition of social interactions in a day-
long first-person video of u social event, like a trip to an amusement park. The location and …

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 …

We present a method to analyze daily activities, such as meal preparation, using video from
an egocentric camera. Our method performs inference about activities, actions, hands, and …

With the proliferation of wearable cameras, the number of videos of users documenting their
personal lives using such devices is rapidly increasing. Since such videos may span hours …

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 …