Selecting a suitable IP Camera Module is the key to ensuring the stable and efficient operation of the non - sensing face recognition attendance access control dome camera. This process needs to comprehensively consider multiple factors such as actual application scenarios, functional requirements and technical parameters to make the module perfectly match the product's positioning and usage needs.
First of all, the hardware performance of the module is the primary consideration. The processor's computing power directly affects the speed and accuracy of face recognition. For scenarios with a large number of people passing through, such as office buildings and industrial parks, it is necessary to choose a processor with sufficient computing power like HiSilicon 3516CV500 with 0.5T computing power to ensure that it can handle the task of detecting about 50 faces per frame at 12 frames per second. The image sensor's performance is equally important. A sensor with wide dynamic range such as Sony IMX327 with 120db can adapt to complex light environments, ensuring that clear face images can be captured even under strong light or backlight, thus avoiding recognition failures caused by blurred images.
Secondly, the image processing and encoding capabilities of the IP Camera Module should be compatible with the product's application requirements. The module needs to support appropriate resolution and encoding formats. Taking 1920*1080@30fps resolution as an example, it can balance image clarity and data volume. At the same time, supporting H.265/H.264 encoding can effectively reduce bandwidth occupation and storage space, which is particularly important for devices that need real - time transmission and long - term storage of video data. For occasions with high concurrency, such as enterprise entrances during peak hours, the module's ability to process multiple faces simultaneously is crucial. It should be able to support simultaneous capture of multiple faces in the same picture, like up to 20 faces, to ensure that no omission occurs when many people pass through at the same time.
In addition, the integration of algorithms and functional scalability of the module are important indicators for selection. The module should be embedded with mature and efficient face detection and recognition algorithms, and have a certain capacity of face database to meet the needs of different scales of application scenarios. For example, supporting 5000 face databases can meet the needs of medium - sized enterprises. At the same time, it should have the function of synchronizing with the attendance database to realize the automatic import of attendance data, which can improve the efficiency of attendance management. The support for SDK in - depth development is also a factor that cannot be ignored, as it allows the module to be flexibly customized and expanded according to specific needs, adapting to more personalized application scenarios.
Finally, the stability and adaptability of the IP Camera Module in practical applications should also be considered. It needs to have a suitable recognition distance range, such as 0.3m~6m, to meet the needs of different passage widths. Moreover, it should be able to work stably for a long time in various environmental conditions, ensuring that the recognition accuracy and response speed are not affected by temperature, humidity and other factors. Only by comprehensively evaluating these aspects can we select an IP Camera Module that truly meets the needs, laying a solid foundation for the excellent performance of the non - sensing face recognition attendance access control dome camera.
