- Quick start
- Download
- Online manual
- Introduction
- Start Onvif programming
- C# Onvif.IP.Camera.Viewer
- C# Onvif IP Camera Viewer Git repository
- IP video camera viewer
- PTZ IP camera motion control
- Onvif network video recorder
- Motion detection and alarms
- IP camera to SIP video call
- Configure Onvif IP cam remotely
- Onvif IP camera video server
- Video stream on website
- Onvif Network Video Analytics
- Events based on changes
- Implement object tracking
- Implement tripwire
- Implement loitering
- Implement take away events
- Leave-behind events
- Number plate recognition
- Object classification
- Onvif IP Camera Manager
- Computer Vision Technology
- Motion recognition and analysis
- Object detection
- Object categorization
- Image Manipulation
- Ozeki SDK for Linux
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Get started
- Download the SDK
- Copy the C# code example into Visual Studio
- Build your IP Camera project
Did you know?
Did you know, that this SDK was used to build Ozeki Camera Recorder?
If you don't want to write code, it could be just what you need. Download it now from the follolwing page: Download Ozeki Camera Recorder.
► Tutorial 9
How to implement Onvif Network Video Analytics in C#
Number plate recognition in C#
Learn about how to implement such great Network Video Analytics (NVA) solutions as number plate recognition. By using OZEKI Camera SDK it is possible to construct an automatized parking ticket vending machine or an automated gate. Start learning here to build it. Start now
Create change-based events in C#
This lecture demonstrates step-by-step how to generate events based on changes in the analyzed video or picture. Build your own alarm system using OZEKI Camera SDK. Start now
Build object classification in C#
In this lecture you can get to know how to make a distinction between a person, vehicle or other objects (object classification). Start now
Implement tripwire in C#
How to identify objects moving in a specified direction as they cross over a line drawn within the IP camera's field of view. Start now
Implement loitering in C#
This lecture shows how to detect when an object remains in a user-defined region of interest (RO) for a configurable length of time. This is a really useful feature when it comes to program a parking lot monitoring system or when you want to identify the potential costumers. Start now
Create leave-behind events in C#
This lecture in intended to explain on how to detect when an object has been left behind or inserted in the full view of an IP camera. Start now
Implement multiple tripwire in C#
From this lecture you can learn how to build a solution
that enables the association between two virtual
tripwires creating an invisible but efficent security zone using OZEKI Camera SDK.
Start now
Create enter / exit event in C#
Get to now how to detect when an object enters or exits a specified region of interest (ROI) within the IP camera's field of view using OZEKI Camera SDK. Start now
Implement occupancy in C#
This lecture demonstrates a C# application that provides information about the number of people in a user-defined region of interest (ROI). It is a really efficent method to control the number of operating cash registers based on the number of costumers. Start now

In this tutorial you can learn more about writing such codes in C#, which handle an IP camera using OZEKI Camera SDK.
In production and marketing point of view, it is really important to map correctly the consumer habits. The OZEKI Camera SDK helps you to perform this analytics. There are several areas, where you can apply it e.g. you can get data about how many customers are there in front of a certain shelf within a certain time period and you can also find out how many of them choose a certain product. The results can be used during the product placement (top or bottom shelf, main or side corridor, next to the checkout, etc), packaging, pricing, etc. You can use your IP camera to monitor remotely and then your system will analyze automatically.
Video analytics has a huge benefit among entry systems as well. Just a simple example: due to the number plate recognition, you can separate those drivers automatically, who paid for the parking and identify those who didn't. Or you can recognize the cars of your workers and identify others with ease.
You will find clear explanation (including code snippets and GUI screenshots) for every examples related to the functionalities mentioned above. The full source code of each example project can be downloaded and the FAQ section gives answers for the most commonly asked questions.
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