Description
Panasonic AW-SF100 / AW-SF200 PTZ Camera Auto Tracking Software / Server
Features
- Motion Detection and Facial Recognition used for high-precision auto tracking with minimum tracking error
- Allows for simultaneous auto tracking and centralized control of multiple cameras
- Various license options available for simplified deployment and system scaling
- Ideal for applications where multiple cameras are deployed across multiple locations such as on a university/corporate campus, a convention center or conference hall
- Compatible with AW-UE70 series, AW-HE130 series and AW-HE40 series PRO PTZ cameras
Specifications
- Supported Cameras: AW-UE70, AW-HE130, AW-HE40, AW-UE150 (future support planned)
- Supported Server:
- Server Configuration: Although this software can operate on a single-server configuration too, the number of remote cameras that can be controlled simultaneously can be increased by configuring the software with multiple servers. Up to four remote cameras can be controlled per one server.
- PC System Requirements: Client PC
- CPU: Core i5-2520M 2.50 GHz or above
- Memory: 4GB or above
- Display: 1920 x 1080 or above
- Web browser: Google Chrome
- Required PC (Server): Server PC
- CPU: Xeon E5-2640 v4 2.40 GHz 1P/10C or above
- Memory: 8 GB or above
- OS: Windows Server 2012 R2
- Network: The Server PC, Client PC, and remote camera must exist on the same network, and a fixed local IP address must be set for each. This software does not operate in the DHCP environment.
- General Specification:
- The below-mentioned environment is necessary for using this software:
- A server PC is a PC for installing this software, and a Client PC is a PC for accessing the server and displaying the GUIs.
PRODUCT DETAILS
Automate your robotic camera operation with AW-SF200, a state-of-the-art auto tracking software option for Panasonic PRO PTZ robotic cameras. Using this software helps dramatically simplify PTZ camera operation in locations such as classrooms, lecture halls, auditoriums, conference rooms and stage environments. Utilizing a combination of tracking methods including body template matching, facial detection and deep learning, cameras can be automated to keep track of a speaker or lecturer, automating camera control while still delivering high production value.
