Qiang Nie

Prof. Qiang Nie

orcid

Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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22 March 2019 in IEEE Transactions on Image Processing
Verified
Journal Article
Closed access
Qiang NieQiang Nie
Qiang Nie
JWJiangliu Wang
Jiangliu Wang
XWXin Wang
Xin Wang
YLYunhui Liu
Yunhui Liu
Skeleton-based human action recognition has been a hot topic in recent years. Most existing researches are based on the skeleton data obtained from Kinect which is noisy and unstable, in particular in the case of occlusions. To cope with the noisy skeleton data and variation of viewpoints, this paper presents a view-invariant method for human action recognition by recovering the corrupted skeletons based on a 3D bio-constrained skeleton model and visualizing those body-level motion features obtained during the recovery process with images. The bio-constrained skeleton model is defined with two types of constraints: 1) constant bone lengths and 2) motion limits of joints. Based on the bio-constrained model, an effective method is proposed for skeleton recovery. Two types of new motion features, the Euclidean Distance Matrix between joints (JEDM) which contains the global structure information of the body, and the local dynamic variation of the joint Euler angles (JEAs), are used in describing human action. These two types of features are encoded into different motion images which are fed into a two-stream convolutional neural network for learning different action patterns. Experiments on three benchmark datasets achieve better accuracy than the state-of-the-art approaches, which demonstrates the effectiveness of the proposed method.


3 February 2023 in International Journal of Computer Vision
Verified
Journal Article
Closed access
PDF file
Qiang NieQiang Nie
Qiang Nie
ZLZiwei Liu
Ziwei Liu
YLYunhui Liu
Yunhui Liu

1 May 2018 in Chinese Journal of Electronics
Verified
Journal Article
Open access
PDF file
YLYunhui Liu
Yunhui Liu
FZFan Zheng
Fan Zheng
RGRuibin Guo
Ruibin Guo
JWJiangliu Wang
Jiangliu Wang
Qiang NieQiang Nie
Qiang Nie
ZWZerui Wang
Zerui Wang
This paper presents a brief review on recent work on machine intelligence for real-world applications of robots. To act in a real world environment, a robot should possess a broad sense of intelligence including speech, perception, reasoning, action, etc. In this paper, we particularly deal with the intelligence involving action or body motion. The intelligence related to robot action/motion can be classified into two categories: manipulation intelligence and mobility intelligence. The manipulation intelligence means the skill/intelligence of reliably manipulating objects according to tasks and the mobility intelligence corresponds to the ability of autonomously moving, or flying, and or jumping in a natural environment. Human-robot interaction is another important topic for real-world applications. In addition to reviewing the major approaches, this paper also gives an overview on our efforts in these important topics.

20 September 2025
Verified
Book Chapter
Closed access
PDF file
YSYong Sun
Yong Sun
YWYipeng Wang
Yipeng Wang
JSJunyu Shi
Junyu Shi
ZZZhiyuan Zhang
Zhiyuan Zhang
YXYanmei Xiao
Yanmei Xiao
Qiang NieQiang Nie
Qiang Nie