An important part of using artificial intelligence (AI) systems, is allowing businesses to be more efficient while the machine works independently. One of the most recognizable parts of such vision services is AI image recognition. This enables the machine to locate, identify and classify objects.

What is video object detection?

Object detection is also known as image detection, object recognition or object identification. Its goal is to answer the question “What objects are in the video, and where are they?”

Video object detection mimics human vision, allowing machines to analyze each frame in a video and identifying the objects present within them. This kind of tool aims to locate and identify objects seen on a video input.

How does video object detection work?

Video object detection classifies instances of visual objects, such as human, vehicles, buildings, animals, etc. As with every other AI solution, the system needs to be “taught” or “trained” to detect objects in a video. To do that, there are some steps that need to be followed:

• Data collection – The first step is to create a video library, preferably matching the actual use case. When all data is collected, guidelines need are created for labeling objects of interest.
• Data labeling – In this stage, bounding boxes are drawn in the entities that we want the AI to identify, with the goal of teaching the machine to recognize those kinds of objects. This step and the previous one are extremely important for correct operations.
• Training – The algorithm is then trained on the labeled data, to ensure accuracy. After the initial training, the performance is evaluated on data that was not included in the initial dataset.
• Testing – In the final step, the machine goes through real-life testing, to determine the accuracy of the results and access if more training is needed. Multiple experiments are conducted, and improvements are made based on feedback.

Use cases for video object detection

There are numerous use cases for video object detection, such as:

• Video surveillance – Security can be improved by using video object detection. Retailers can have their shops and warehouses equipped with the system to alert security in cases of theft. It can also be used to monitor safety and employee performance.
• Traffic analysis – By having vehicles counted in roads and car parks, traffic jams can be avoided, and parking solutions can be optimized. This data can also be used for road construction, maintenance, and improvement.
• Text detection – Number plate recognition can be used to provide accesses to authorized vehicles, vehicle location and tracking.
• Face detection – There are already various uses for this, even in daily life, with social network filter that follow faces around, and automated security systems that lock or unlock accesses using facial recognition.

AID.VISION – Automatic detection of incidents on roads

The AID.VISION is a solution powered by Artificial Intelligence systems, which automatically detects various types of incidents and triggers real-time alerts to an operations center.

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