Face Recognition Web App

Job Description:

Only highly experienced people may bid here.

25% of the total amount will be given to you after you complete 50% of the total work. No amount will be increased for this project at any cost. No project will be awarded or no milestone will be released without checking your work on my project.

Our app could be used for eKYC verification using Aadhaar Card Number, PAN Number, Voter Card, Driving License. Where we will upload the image or small video of the i.d card holder into the database and one i.d proof of that person, then app should be able to detect the face of the person and verify that person's photo and his photo i.d proof is same.

App should be able to detect colors, weather, activities and moments also through live CCTV Camera feed.

Our professional users should be able to use this technology to find suspects within sometime of an incident, out of thousands of hours of footage from diverse camera feeds. This same accuracy is now available to your home and business customers to make their own video footage more useful, usable and relevant.

We need these features to be added into our app.

We should be able to have the automatic ability to classify and refine query results by object types, such as people, vehicles, packages, etc.

Users should be able to submit queries such as “show me trucks” or “show me people wearing red.”

Every new feature creates superb differentiated value, unique to each partner’s needs.

Quick review

This should not be fast forward: it’s all in one rapid video review.

Advance scheduling

Proactive rapid video review to “know what you didn’t know before”

Deep drill down

We should be able to Search the day in minutes. Select events and access the original video in a single click.

Alert configuration

It should Send notification of unusual activity.

Gain insights

There should be a feature of Graphic visualisation of data analysis (heat maps, pathways, bar graphs, etc.)

Share clips

Users should be able to One-click export of video clips to email or social media.

Filtering out noise to know what’s important.

To limit the false detection of new objects in a frame, we’ve learned how to filter out the movements in the environment – such as branches, shadows, reflections, waves and clouds.

Handling complex lighting conditions on the fly.

Every scene is different- we’ve developed the capacity over the years to handle thousands of scenes.

Lighting conditions and weather conditions for example (you’d be surprised how snow and rain impacts the accuracy of computer vision!).

Detecting subtle and camouflaged objects.

We can identify very small subtle objects, down to the level of small creature. and, while an object in the frame that is appearing against a background of the same color is a difficult task – over the years, our detection has become very sensitive to subtle differences in color and texture.

Knowing what goes together to create a single incident.

If a person “disappears” from the frame for a period of several seconds, as they pass behind a car or a tree, we detect that and treat it as one incident. If the person goes in and out of the frame boundaries, we treat it as separate object incidents.

Extended capabilities through third party metadata.

We connect video time stamps to metadata from other systems to create tight custom integrations.

For example, if you have an ID badge system in your small business application, we can pair that information to video.

The same goes with audio feeds, motion sensors, smoke detectors and more.

There should be an admin account and user account.

Admin should be able to monitor any user account parallelly.

Admin should have rights to add or remove any user.

There should be a key from Admin side and after submitting that key only, user account will be activated.

We need to embed the app on our drone and will take it towards some public meeting and app shud be able to recognise the number of people available in crowd and recognise their face.

Not only do you have the alert from the third party feed, but the video of what happened at that exact moment, along with more efficient presentation and rich query formulation capabilities.

Habilidades: Inteligência Artificial, Programação C++ , Machine Learning (ML)

Sobre o Cliente:
( 10 comentários ) New Delhi, India

ID do Projeto: #14560687

5 freelancers estão ofertando em média ₹27803 nesse trabalho


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