摘要人体行为识别是计算机视觉领域的一个研究热点, 具有重要理论价值和现实意义. 近年来,
为了评价人体行为识别方法的性能, 大量的公开数据集被创建. 本文系统综述了人体行为识别 …

Conventional feature selection methods select the same feature subset for all classes, which
means that the selected features might work better for some classes than the others …

为提高多视角人体动作识别的精度, 提出了一种新的深度神经网络模型——CNN+ CA
(Convolutional Neural Network plus Context Attention) 模型和一种基于序列匹配的识别方法 …

This paper proposes a novel algorithm for computing discriminative descriptors named as a
sparse coded composite descriptor (SCCD) for robust human activity recognition. The …

We present a new method for tracking human pose by employing max-margin Markov
models. Representing a human body by part-based models, such as pictorial structure, the …

We investigate the tracking of 2-D human poses in a video stream to determine the spatial
configuration of body parts in each frame, but this is not a trivial task because people may …

A novel deep neural network named CNN+ CA (Convolutional Neural Network plus Context
Attention) model is constructed and a new recognition algorithm based on sequence …

Cinematic Shot Attribute Analysis aims to analyze the intrinsic attributes of movie shots, such
as movement and scale. In previous methods, specialized architectures were designed for …

In this paper we will experimentally prove that after recalculating the motion capture
(MoCap) data to position-invariant representation it can be directly used by classifier to …

Recognizing human actions in videos is an active topic with broad commercial potentials.
Most of the existing action recognition methods are supposed to have the same camera view …