Webcam to IP Camera Software

CCTV Software uses IP cameras and webcams to perform unbeatable video monitoring. Video stream can be viewed from many sources simultaneously. The program supports more than 1000 models of IP cameras, and virtually all webcams. You can record the events in your home or office while you are away. Motion detector is based on video frame analyzing algorithm. You can use it to protect your home from intruders. The motion sensor are fully customizable so you can be sure you will not get the false alerts. If CCTV Software detects motion, it can send you an alert message in telegram messenger, with attached video from cameras. It is not only important to identify the security threat, but also to capture the evidence. When the program detects the motion, it can make snapshots on cameras, and to record video. If you are a boss, you can schedule recording the video in your office rooms and then watch it later, to make sure your employees do the job. The video player allows you to playback recorded video anytime. The captured media files are saved to the local folder, or on the cloud.

We use a special module for reading the video stream to queue the received frames for faster processing. From the queue, the frame is redirected and processed by the face detector and feature extraction tool, the output is a feature vector, which is later stored in the database. Integrated similarity measurement algorithms are used to compare newly acquired feature vectors with those stored in the database to determine if a person exists in the database or not.

Computer vision technology of today is powered by deep learning algorithms that use a special kind of neural networks, called convolutional neural network (CNN), to make sense of images. These neural networks are trained using thousands of sample images which helps the algorithm understand and break down everything thats contained in an image. These neural networks scan images pixel by pixel, to identify patterns and memorize them. It also memorizes the ideal output that it should provide for each input image (in case of supervised learning) or classifies components of images by scanning characteristics such as contours and colors. This memory is then used by the systems as the reference while scanning more images. And with every iteration, the AI system becomes better at providing the right output.

The video surveillance software market has been plagued with challenges for a long time, which include intricate setups, the need for resource-intensive external libraries, and non-standard compliance by many IP camera manufacturers. Most existing systems are burdened with issues accumulated from years of open-source solutions development, reflecting on their compatibility and stability.
Our company has been continuously striving to develop a stable system for working with IP cameras and processing video streams. The challenge is to create a universal solution that isnt tied to a specific IP camera manufacturer.

One notable issue is that the FFmpeg development for 32-bit systems has been discontinued for a while. Many users still want to repurpose older computers, which are adequate for video recording and intelligent detection. Therefore, there are many outdated systems on the market, the core of which was developed 10-15 years ago, with interfaces that often appear outdated. New systems target 64-bit architectures and newer, more expensive hardware but often remain unstable over long operations.