Videos

Facial Expression Recognition with Skip-Connection to Leverage Low-Level Features

Deep convolutional neural networks (CNNs) have established their feet in the ground of computer vision and machine learning, used in various applications. In this work, an attempt is made to learn a CNN for a task of facial expression recognition …

Inferring what the videographer wanted to capture

Detecting important regions in videos has been extensively studied for past decades for their wide variety of applications including video summarization and retargeting. Visual attention models draw much attention for this purpose, which find …

Markov random field-based real-time detection of intentionally-captured persons

Most videos taken by videographers contain intentionally-captured persons (ICPs), who are essential for what the videographers want to express in their video. This paper presents a method to detect ICPs in real-time. Whether a person in a video is an …

Discriminating intended human objects in consumer videos

In a consumer video, there are not only intended objects, which are intentionally captured by the camcorder user, but also unintended objects, which are accidentally framed-in. Since the intended objects are essential to present what the camcorder …