A Novel Human Pose Detection from Videos Algorithm Based on Motion Capture Data

2010 ◽  
Vol 20-23 ◽  
pp. 833-837
Author(s):  
Ou Yang Yi
Keyword(s):  
Human Body ◽  
Feature Matching ◽  
Detection Algorithm ◽  
Recognition Algorithm ◽  
Pose Recognition ◽  
Pose Detection ◽  
Spatio Temporal ◽  
Human Pose ◽  
Static Background ◽  
Change Monitoring

This video image of static background frame and deduction, the pixel, pixels for sports change monitoring and static pixels. By combining the feature of deformation of human body positioning movement of template, the human body pose detection algorithm put in spatio-temporal detection to human pose recognition using feature matching, accelerate matching speed probability. This method in the testing result is superior to other pose recognition algorithm, and also has the ability to quickly identify.

scholarly journals Human body pose detection using Bayesian spatio-temporal templates

2006 ◽  
Vol 104 (2-3) ◽  
pp. 127-139 ◽  
Author(s):  
M. Dimitrijevic ◽  
V. Lepetit ◽  
P. Fua
Keyword(s):  
Human Body ◽  
Pose Detection ◽  
Spatio Temporal

scholarly journals An Efficient Way to Recognize a Person in Surveillance Video

2020 ◽  
Author(s):  
Sowmiya V ◽  
Malathi S
Keyword(s):  
Elderly People ◽  
Human Body ◽  
Surveillance System ◽  
Fall Detection ◽  
High Accuracy ◽  
Visual Surveillance ◽  
Surveillance Video ◽  
Pose Detection ◽  
Human Pose ◽  
Artificial Neural Network Ann

This paper is presented for tracking a person in the visual surveillance system and to detect the pose of that particular person presented in that video. This concept is fully based on monitoring elderly people, patients, and people with disabilities. In the present day monitoring them for the whole day has been difficult and high-end surveillance is also difficult. So automatic pose detection makes these tasks easier. The algorithm presented here not only recognize human pose like running, walking but also includes abnormal pose detection like fall detection for elderly people, people with chronic disease are suffering from strokes and often fell down , the algorithm can also detect the various pose of a human. Although the technique to find human pose are existing but detecting human pose in surveillance system are difficult due to its movement presented in the video. In particular, we demonstrated by separating the motion pixel by (MPEM) pixel expectation maximization. (MPEM) is the process of separating the movement pixel. Finally KL transform is applied to track the action and pose of a human. The kinetic sensor SDK used to recognize the human body with high accuracy and more efficiency. Human body and face authentication modality are performed using various methods such as artificial neural network (ANN). Several experiments are performed to validate the effectiveness are performed to validate the effectiveness of the proposed system tracking approach, the result of which seems quite promising.

scholarly journals A Quasi-Hole Detection Algorithm for Recognizing k-Distance-Hereditary Graphs, with k < 2

Algorithms ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 105
Author(s):  
Serafino Cicerone
Keyword(s):  
Polynomial Time ◽  
Detection Algorithm ◽  
Recognition Algorithm ◽  
Forbidden Subgraphs ◽  
Induced Subgraph ◽  
Hole Detection

Cicerone and Di Stefano defined and studied the class of k-distance-hereditary graphs, i.e., graphs where the distance in each connected induced subgraph is at most k times the distance in the whole graph. The defined graphs represent a generalization of the well known distance-hereditary graphs, which actually correspond to 1-distance-hereditary graphs. In this paper we make a step forward in the study of these new graphs by providing characterizations for the class of all the k-distance-hereditary graphs such that k<2. The new characterizations are given in terms of both forbidden subgraphs and cycle-chord properties. Such results also lead to devise a polynomial-time recognition algorithm for this kind of graph that, according to the provided characterizations, simply detects the presence of quasi-holes in any given graph.

Two-Dimensional Image Based Product Connector Recognition for Robotic Disassembly in Remanufacturing

2021 ◽  
Author(s):  
Yang Hu ◽  
Yalin Wang ◽  
Feng Xu ◽  
Bitao Yao ◽  
Wenjun Xu ◽  
...  
Keyword(s):  
Template Matching ◽  
Search Strategy ◽  
Feature Matching ◽  
Resource Conservation ◽  
Recognition Algorithm ◽  
Two Dimensional ◽  
Crucial Step ◽  
Two Dimensional Image ◽  
Disassembly Process ◽  
Robotic Disassembly

Abstract Remanufacturing has received increasing attention for environmental protection and resource conservation considerations. Disassembly is a crucial step in remanufacturing, is always done manually which is inefficient while robotic disassembly can improve the efficiency of the disassembly. Aiming at the problem of product connector recognition during the robotic disassembly process, we analyze the template matching and feature matching principles based on two-dimensional images. To reduce the computational complexity of traditional template matching, a stepwise search strategy combining coarse and fine is proposed. Based on this a product connector recognition algorithm based on fast template matching and a product connector recognition algorithm based on feature matching is designed. Taking bolts and hexagon nuts as examples, the recognition effects of the two algorithms are compared and analyzed.

Sign in / Sign up

Export Citation Format

Share Document