human action recognition by learning bases of action attributes and parts l.
Download
Skip this Video
Loading SlideShow in 5 Seconds..
Human Action Recognition by Learning Bases of Action Attributes and Parts PowerPoint Presentation
Download Presentation
Human Action Recognition by Learning Bases of Action Attributes and Parts

Loading in 2 Seconds...

play fullscreen
1 / 10

Human Action Recognition by Learning Bases of Action Attributes and Parts - PowerPoint PPT Presentation


  • 259 Views
  • Uploaded on

Human Action Recognition by Learning Bases of Action Attributes and Parts. Bangpeng Yao, Xiaoye Jiang, Aditya Khosla , Andy Lai Lin, Leonidas Guibas , and Li Fei-Fei Stanford University. Outline. Introduction Action Bases

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'Human Action Recognition by Learning Bases of Action Attributes and Parts' - maleah


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
human action recognition by learning bases of action attributes and parts

Human Action Recognition by Learning Bases of Action Attributes and Parts

Bangpeng Yao, Xiaoye Jiang, AdityaKhosla, Andy Lai Lin, LeonidasGuibas, and Li Fei-Fei

Stanford University

outline
Outline

Introduction

Action Bases

Learning the Dual-Sparse Action Bases and Reconstruction Coefficients

Experiments

introduction
Introduction
  • Human action recognition in still images
    • A general image classification problem
    • Human-object interaction
    • Parts + Attributes
  • Contributions
    • Represent each image by using a sparse set of action bases that are meaningful to the content of the image
    • Effectively learn these bases given far-from-perfect detections of action attributes and parts without meticulous human labeling
action bases
Action Bases
  • Attributes and parts
    • Attributes: verb, learned by discriminative classifiers
    • Parts: object parts and poselets, learned by pre-trained object detectors and poselet detectors
    • A vector of the normalized confidence scores obtained from these classifiers and detectors is used to represent this image.
action bases5
Action Bases

High-order interactions of image attributes and parts

is used to represent each image and SVMs are trained for action classification

experiments
Experiments
  • PASCAL actions
  • Stanford 40 actions