Semantic Segmentation Annotation Tool
Boost your ROI by always finding the right sequence
Image segmentation is a very long task that can be extremely costly if done with unadapted tools. But it doesn’t have to be that way.
Perfect Memory’s semantic segmentation annotation tool provides its users with smart, accurate and intuitive image segmentation. It then interprets the retrieved data and makes it exploitable, to simplify your teams’ work and significantly improve your ROI.
What is image segmentation?
Here is an introduction to the image segmentation process and how Perfect Memory transcends it to make your video data more exploitable than ever.
Image segmentation is the process used to divide a visual content into different sections according to the features you can find in it. It is able to identify named entities, annotate and classify them to facilitate their retrieval.
While some softwares allow to automatically or manually segment and label contents, leaving you with raw data, Perfect Memory goes further and combines this functionality with artificial intelligence to analyze and understand this information and make it truly useful for your business.
How does it work?
A semantic segmentation annotation tool uses instance identification to detect all the entities (places, people or objects) present in a video content, then label and categorize them.
Using the power of semantics and artificial intelligence, it provides automated instance detection and tagging to identify and classify objects with pixel level accuracy.
Perfect Memory’s semantic segmentation tool then interprets these datasets using rule-based machine learning algorithms, in order to provide the user with the most relevant and precise information possible about their content.
What are the key features?
The main features you can find in a segmentation annotation tool are :
- Classification: allows to recognize objects present in a frame and categorize them in classes (e.g. “car”)
- Object detection: finds out where these objects are in the picture and annotates them
- Image segmentation: detects with pixel precision every object belonging to the assigned classes
- Instance segmentation: attributes an ID to each object of a same class (e.g. “car 1”, “car 2”, etc.)
After the segmentation part, which consists in dividing the content into homogeneous sections, comes the annotation feature, whichs allows to extract and recognize any visual instance then automatically label it.
Why should you use semantic segmentation?
Semantic segmentation is a powerful tool that helps you optimize how you distribute and monetize your contents. It uses deep learning algorithms to bring you the exact information you need about your video content, saving you time and money.
Moreover, a semantic segmentation annotation tool helps you improve your content’s accessibility for every audience, by generating audiodescription for example.
By segmenting precise sections in your content based on relevant data, it allows you to easily access the exact video segment you’re interested in.
How to use semantic segmentation?
Our segmentation annotation tool is incredibly easy to use. In fact, you don’t need to do much: our machine learning tools handle all the data processing.
The extraction and processing of a great amount of data allows the connector to train its recognition and categorization models, making it capable of understanding and classifying various parameters within a content.
Semantic segmentation use cases
Semantic segmentation can be a great help for all kinds of businesses.
For example, in media and news companies, our tool is able to identify the report segments and distinguish them from segments where the host is appearing. It can then index the full program, divide it into relevant sections and precisely describe each one.
Using state-of-the-art machine learning models, Perfect Memory’s segmentation tool can tell which guests are involved, which subjects they are discussing, analyze the feedbacks on the report, whether copyrights are applicable in certain sections, and much more.
How does Perfect Memory’s semantic segmentation tool help me reach my goals?
Our semantic segmentation annotation tool not only categorizes all of the data on your video file, it also interprets the segmentation results and processes this knowledge to apply it to your business. In other words, it turns raw data into truly exploitable, ready-to-use information.
Integrated into Perfect Memory’s DAM-as-a-Brain solution, it helps you boost your ROI by always finding the right sequence that is useful to your company and easily share it with your clients.
Our Semantic Segmentation Annotation Tool
Our semantic segmentation tool saves the work of computer vision teams. It complements with a video analysis functionality to fully exploit your video content. The speech-to-text feature will allow to generate captions and retrieve the exact terms you need in a participant’s speech.
Our tool understands many different language through natural language processing, like speech-recognition on a speaker during an international conference.
Finally, Perfect Memory brings named entity recognition to a new level with the help of artificial intelligence and neural networks.