Opendata, web and dolomites

SensifAI SIGNED

Understanding Videos Automatically with the SensifAI Deep Learning Technology

Total Cost €

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EC-Contrib. €

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Partnership

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 SensifAI project word cloud

Explore the words cloud of the SensifAI project. It provides you a very rough idea of what is the project "SensifAI" about.

videos    imaging    camera    zurich    marketplace    scenes    mobile    genre    moods    international    texts    delivers    80    emerge    emotion    logos    scene    searchable    web    audio    recognizing    audios    managed    trillion    captured    became    recognition    leuven    millions    visual    believe    landmark    alumni    imagine    recognizes    people    wearable    tagging    environment    day    involvement    learning    edge    content    bvba    recognize    million    contents    actions    tags    cloud    scientists    internet    01    europeans    starting    software    data    acquired    describing    ranging    microphone    ku    automatically    traffic    description    follow    pricing    landmarks    aurally    mit    amazon    visually    accumulative    minute    sport    limited    eth    customized    manually    celebrities    extremely    05    accurately    unsafe    model    119    deep    video    contextual    speech    similarly    tag    google    objects       equipped    services    trained    cutting    founded    impaired    images    music    sensifai    surrounding    semantic    automated    helping    smartphones    action    oem   

Project "SensifAI" data sheet

The following table provides information about the project.

Coordinator
SENSIFAI 

Organization address
address: DREVE DE NIVELLES 182/9
city: BRUSSELS
postcode: 1160
website: n.a.

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Belgium [BE]
 Project website https://sensifai.com/
 Total cost 71˙429 €
 EC max contribution 50˙000 € (70%)
 Programme 1. H2020-EU.3. (PRIORITY 'Societal challenges)
2. H2020-EU.2.3. (INDUSTRIAL LEADERSHIP - Innovation In SMEs)
3. H2020-EU.2.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies)
 Code Call H2020-SMEInst-2018-2020-1
 Funding Scheme SME-1
 Starting year 2018
 Duration (year-month-day) from 2018-12-01   to  2019-05-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    SENSIFAI BE (BRUSSELS) coordinator 50˙000.00

Map

 Project objective

Google has a value of $1 trillion because it has managed to make texts searchable. However, 80% of internet traffic is videos, audios and images and they are not searchable. Making videos searchable is extremely challenging. This is why most of the video tagging is done manually and the results in automated video recognition are still limited. Mobile video recognition is also starting to emerge. SensifAI has developed a cutting-edge audio-visual deep-learning technology trained on millions of videos to recognize audio and video content and to tag them accurately. SensifAI automatically tags videos, images and audio, which makes them searchable and can be customized for a range of use cases. We believe our approach to contextual video analysis is unique and on the leading edge as it recognizes, scenes, actions, celebrities, landmarks, logos, music genre, moods and emotion and speech. SensifAI delivers the video recognition technology on the cloud on the Amazon Web Services Marketplace and can be embedded on devices such as smartphones (by OEM’s). Our software just became available on the Amazon Web Services Marketplace where we follow a unit-based pricing model ranging from €0.01/minute for recognizing landmark images/objects/celebrities/unsafe contents to €0.05/minute for general tagging and action/sport recognition. SensifAI bvba was founded by three alumni and scientists from MIT, ETH Zurich and KU Leuven, who acquired an accumulative experience in audio-visual data processing through involvement in many international projects. Imagine a day when the 30 million visually impaired Europeans use a wearable camera equipped with a software describing them the surrounding environment automatically by recognizing the semantic concept of the captured video. includes the description of the scene, objects, and activities. Similarly, imaging a technology when the 119 million aurally impaired people use a wearable microphone equipped with a software helping them.

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The information about "SENSIFAI" are provided by the European Opendata Portal: CORDIS opendata.

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