Video annotation means shaping outlines and adding comments or elements on videos split into frames (images). This process is possible because of the combination of human labeling and video annotation software. People create gigabytes of training datasets for computer vision. So only with high-quality video annotation Machine Learning algorithms can adequately identify similar objects on new videos.
But finding experienced video annotators with industry-relevant skills is challenging. Some companies don’t give you enough control over your team, while others offer high rates for workers located in totally different time zones. However, our outsourcing model helps you find the solution for your budget and requirements. We’ll build your managed video labeling team within several weeks.
Only with top-notch video annotation deep learning models can learn from the best. And that’s how video labeling practitioners we hire can process your datasets:
The teams we build ensure accurate marking of the bounding boxes' edges. They also minimize variations of box sizes and overlaps in your training data. This is critical to keep your model effective. And if overlapping is unavoidable, the professionals we hire will use more accurate techniques.
With advanced video streaming tools, your labelers will create frames with original resolution. And AI algorithms will help to accurately mark the dimensions of volumetric objects and estimate their hidden parts. This way, our specialists work quickly, spending around half a second per frame.
Polygonal tagging is much more accurate compared to 2D and 3D bounding boxes. So if you need to eliminate the "noise" in your videos, your team will use polygons to mark objects’ boundaries. This type of labeling requires skills and experience, which the professionals we hire have.
This labeling method is also called dot annotation. That's because data labelers use dots to mark small objects or locate points on objects. This technique helps streamline face recognition and pose detection software. Annotators place dots across faces to show emotional expressions or place points along bodies and connect them like a skeleton.
Tagging lines and floor markings on video datasets will teach machines at stocks to move items safely. Broken lanes, sidewalks, roadside edges, travel lanes, and other straight and curved lines will help self-driving AI understand road surface marking.
The classification of video content is split into the classification of image stacks. Professionals apply and extrapolate hundreds of tags, collaborating in real-time with other team members to perform tasks. This service helps deep learning models track activity, recognize human gestures, and detect motion on video streams.
Why choose us? Here are the key benefits you get when contracting us for video labeling services:
Small, mid-sized, and large corporations can find suitable cooperation models with us. Businesses can hire part or full-time annotators or outsource a dedicated video data labeling team. If you decide to add more data tagging specialists, you can do it anytime. We'll initiate a new recruiting process and onboard new people within several weeks.
Hiring video labelers in the US or Western Europe implies significant payroll expenses. But our clients can save up to ⅕ of these costs by hiring skilled annotation experts from Ukraine. That's because the living index in Kyiv is much lower than in the USA, Netherlands, Germany, France, Switzerland, and other EU countries.
Whether you need high-quality audio annotation video labeling, or text tagging services, our recruiters will help you start processing raw data ASAP. That's due to the talent pools our recruiters create. These lists comprise CVs of top video annotation specialists ready to start working soon. Moreover, our specialists use top-notch tools and approaches that streamline candidates’ searches.
One of the most appealing advantages of the outsourcing model is that you'll have to handle only business-related tasks. Our managers will resolve all organizational issues for your team. This includes signing employment contracts, office rent, equipment purchase, team building, salary payments, tax report submission, etc. This approach lets project owners concentrate on work.
A video labeling company or agency won't give you as much control as you get with us. Those companies will often charge you per particular work volume, and you'll have to discuss each piece of work with team managers. With us, you're the one who sets tasks for video annotators and pays a fixed fee.
Every video annotating practitioner we hire for you can understand and speak English well. Our recruiters always pay attention to the English level of candidates. And only applicants with B1 pass the pre-screening. This way, we ensure our clients and their teams communicate effectively.
Get in Touch for Top-Notch Video Annotation Service!
At this point, you might be interested in how we collaborate with clients. And below are three basic formats for hiring video data labeling practitioners:
We’ll be glad to cover your needs if you require a team of three or ten video labelers. These specialists will work full-time for your computer vision project(s), and you can assign tasks to them directly. The managed service format is suitable for ongoing Machine Learning projects that regularly need training datasets.
As you select all the candidates, we hire and onboard them for you. Also, we rent office premises and buy equipment for your video annotators.
If the daily video tagging workload is bearable by one professional, your ideal option is outsourcing one labeler. This person will be dedicated to your assignments for 40 hours a week and available during business hours. However, you can agree on the working schedule suitable for you.
Once you hire a full-time annotator, we will handle all the administrative tasks and send you a monthly invoice. And if you need more working hands, you can employ more labelers at any moment.
Startups or small computer vision projects will benefit from this offer. A part-time worker will embrace video annotation for Machine Learning models doing the job for several hours a day. This cost-effective option will fit new companies’ tight budgets and allow them to pay for as much service as they need.
The part-time format assumes we charge you hourly and send you monthly invoices. We still cover all related admin issues and, of course, remain flexible in scaling your team up.
The video labeling professionals we hire prepare training datasets for various AI projects. Agriculture, self-driving, security, insurance, healthcare, and commerce are the key industries that regularly require video annotation services.
During the first call, our managers explore your project and needs. We agree on the job description, budget, and hiring terms. Then our recruiters start searching for candidates and send you CVs. They interview selected applicants and show you the shortlist — you have to choose the future teammates. As candidates respond to job offers, we sign employment contracts with them.
Our video annotation outsourcing format is flexible. So you can start with hiring a part-time data labeler and switch to this person’s full-time employment, for example, in a month. And if you need to add more video annotation specialists, our recruiters will initiate a new search and repeat all the steps.
You pay only once your team is assembled. After we learn your requirements, our recruiters start sourcing candidates. They pre-screen and interview applicants, and you’re welcome to join them anytime. When we finalize the list and get positive responses to job offers, you get a monthly invoice. Once paid, we initiate the hiring process.
In Ukraine. We’re a Kyiv-based company that helps clients outsource video annotation services from local professionals. So your data labelers will be from Ukraine.
Yes. You get complete control over your video labeler or the entire team. So you manage task assignments and prioritize, put on hold, add, or cancel them. Outsourced annotation practitioners work remotely as your employees so that you can engage them in any computer vision video annotation projects. The only requirement is not to exceed the number of working hours per day.
