Motion analysis via feature point tracking technology

Yu Shin Lin, Shih Ming Chang, Joseph C. Tsai, Timothy K. Shih, Hui Huang Hsu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, we propose a tracking method via SIFT algorithm for recording the trajectory of human motion in image sequence. Instead of using a human model that present the human body to analyze motion. Only exact two feature points from the local region of a trunk, one for joints and one for limb. We calculate the similarity between two features of trajectories. The method of computing similarity is based on the "motion vector" and "angle". We can know the degree of the angle by the connect line from joint to limb in a plane which is using the core of object to be the center. The proposed method consists of two parts. The first is to track the feature points and output the file which record motion trajectory. The second part is to analyze features of trajectory and adopt DTW (Dynamic Time Warping) to calculate the score to show the similarity between two trajectories.

Original languageEnglish
Title of host publicationAdvances in Multimedia Modeling - 17th International Multimedia Modeling Conference, MMM 2011, Proceedings
Pages296-303
Number of pages8
EditionPART 2
DOIs
StatePublished - 2011
Event17th Multimedia Modeling Conference, MMM 2011 - Taipei, Taiwan
Duration: 5 Jan 20117 Jan 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume6524 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference17th Multimedia Modeling Conference, MMM 2011
Country/TerritoryTaiwan
CityTaipei
Period5/01/117/01/11

Keywords

  • motion analysis
  • object tracking
  • SIFT

Fingerprint

Dive into the research topics of 'Motion analysis via feature point tracking technology'. Together they form a unique fingerprint.

Cite this