Dataconomy
  • News
  • AI
  • Big Data
  • Machine Learning
  • Trends
    • Blockchain
    • Cybersecurity
    • FinTech
    • Gaming
    • Internet of Things
    • Startups
    • Whitepapers
  • Industry
    • Energy & Environment
    • Finance
    • Healthcare
    • Industrial Goods & Services
    • Marketing & Sales
    • Retail & Consumer
    • Technology & IT
    • Transportation & Logistics
  • Events
  • About
    • About Us
    • Contact
    • Imprint
    • Legal & Privacy
    • Newsletter
    • Partner With Us
    • Writers wanted
Subscribe
No Result
View All Result
Dataconomy
  • News
  • AI
  • Big Data
  • Machine Learning
  • Trends
    • Blockchain
    • Cybersecurity
    • FinTech
    • Gaming
    • Internet of Things
    • Startups
    • Whitepapers
  • Industry
    • Energy & Environment
    • Finance
    • Healthcare
    • Industrial Goods & Services
    • Marketing & Sales
    • Retail & Consumer
    • Technology & IT
    • Transportation & Logistics
  • Events
  • About
    • About Us
    • Contact
    • Imprint
    • Legal & Privacy
    • Newsletter
    • Partner With Us
    • Writers wanted
Subscribe
No Result
View All Result
Dataconomy
No Result
View All Result

The Grammar of Movement- MIT Present Video Recognition Programme

by Eileen McNulty
May 16, 2014
in Data Science, Machine Learning, News
Home Topics Data Science
Share on FacebookShare on TwitterShare on LinkedInShare on WhatsAppShare on e-mail

Hamed Pirsiavash, a postdoctoral scholar from MIT, is developing a new activity-recognition algorithm to identify what’s happening in video files. Pirsiavash and his former thesis advisor, Deva Ramanan of the University of California at Irvine, will present the video recognition programme at the Conference on Computer Vision and Pattern Recognition in June. In a similar fashion to the AlchemyVision Image-Processing software, Pirsiavash’s programme also draws on natural language processing techniques, in that it analyses small parts of a sequence to uncover what is happening in the larger context.

“One of the challenging problems they [NLP researchers] try to solve is, if you have a sentence, you want to basically parse the sentence, saying what is the subject, what is the verb, what is the adverb,” Pirsiavash says. “We see an analogy here, which is, if you have a complex action — like making tea or making coffee — that has some subactions, we can basically stitch together these subactions and look at each one as something like verb, adjective, and adverb.”

For each new action, Pirsiavash and Ramanan’s algorithm must learn a new set of ‘grammar’, or subactions that comprise the whole. The algorithm is not wholly unsupervised; they feed the algorithm a set of videos depicting the same action and specify how many subactions the algorithm should identify, but not what the subactions are.

Although there are several companies working on video-processing programmes, (including Dropcam, who are particularly interested in distinguishing normal and anomalous actions), Pirsiavash and Ramanan’s has several advantages. First, the time it takes to analyse a video is on a linear scale; if a video is 10 times as long, it takes 10 times as long to process (rather than 1,000 times longer, as was the case with previous algorithms). Secondly, its comprehension of subactions means it’s able to identify partially-completed actions, and doesn’t have to wait until the end of video clip to deliver results. Third, the amount of memory required to run the algorithm is fixed; it doesn’t require any more space to process lengthier or larger clips.

Looking forward, Pirsiavash is particularly excited about possible medical applications of the programme. For instance, they might be able to teach the programme the grammar of properly- and improperly-executed physical therapy exercises, or distinguish whether a patient has remembered or forgotten to take their medicine.


Join the Partisia Blockchain Hackathon, design the future, gain new skills, and win!


Read more here.
(Image source: MIT website)


Interested in more content like this? Sign up to our newsletter, and you wont miss a thing!

[mc4wp_form]

Tags: Machine LearningMITNatural Language ProcessingVisual computing

Related Posts

What is ChatGPT Plus, and how to get it? Learn its features, price, and how to join ChatGPT Plus waitlist. Is it worth it? Keep reading and find out

ChatGPT Plus: How does the paid version work?

February 2, 2023
AI Text Classifier: OpenAI's ChatGPT detector can distinguishes AI-generated text

AI Text Classifier: OpenAI’s ChatGPT detector indicates AI-generated text

February 2, 2023
BuzzFeed ChatGPT integration: Buzzfeed stock surges in enthusiasm over OpenAI

BuzzFeed ChatGPT integration: Buzzfeed stock surges after the OpenAI deal

February 2, 2023
Adversarial machine learning 101: A new frontier in cybersecurity

Adversarial machine learning 101: A new cybersecurity frontier

January 31, 2023
What is the Nvidia Eye Contact AI feature? Learn how to get and use the new Nvidia Broadcast feature. Zoom meetings and streams get easier.

Nvidia Eye Contact AI can be the savior of your online meetings

February 2, 2023
How did ChatGPT passed an MBA exam

How did ChatGPT passed an MBA exam?

February 2, 2023

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

LATEST ARTICLES

Cyberpsychology: The psychological underpinnings of cybersecurity risks

ChatGPT Plus: How does the paid version work?

AI Text Classifier: OpenAI’s ChatGPT detector indicates AI-generated text

A journey worth taking: Shifting from BPM to DPA

BuzzFeed ChatGPT integration: Buzzfeed stock surges after the OpenAI deal

Adversarial machine learning 101: A new cybersecurity frontier

Dataconomy

COPYRIGHT © DATACONOMY MEDIA GMBH, ALL RIGHTS RESERVED.

  • About
  • Imprint
  • Contact
  • Legal & Privacy
  • Partnership
  • Writers wanted

Follow Us

  • News
  • AI
  • Big Data
  • Machine Learning
  • Trends
    • Blockchain
    • Cybersecurity
    • FinTech
    • Gaming
    • Internet of Things
    • Startups
    • Whitepapers
  • Industry
    • Energy & Environment
    • Finance
    • Healthcare
    • Industrial Goods & Services
    • Marketing & Sales
    • Retail & Consumer
    • Technology & IT
    • Transportation & Logistics
  • Events
  • About
    • About Us
    • Contact
    • Imprint
    • Legal & Privacy
    • Newsletter
    • Partner With Us
    • Writers wanted
No Result
View All Result
Subscribe

This website uses cookies. By continuing to use this website you are giving consent to cookies being used. Visit our Privacy Policy.