Abstract

• Lens Quality: The performance of an AI auto-tracking camera depends on three key factors – focal length, aperture size, and a zoom lens.
• Sensor Size: Larger sensors capture more light, performing better in low-light environments. Smaller sensors are prone to image noise in dark settings.
• Focal Length & FOV: Shorter focal lengths provide a wider field of view (FOV), while longer focal lengths result in a narrower FOV.
• Application: Choose a short focal length for wide-angle coverage. For clear facial recognition at a distance, select a camera with high optical zoom (e.g., 20x or 30x).

Understanding the Lens of an AI Auto-Tracking Camera

The lens acts as both the "eye" and the "magnifying glass." It determines how far, how wide, and how bright the camera can see. Quality is generally determined by lens grinding, optical coating, and surface smoothness.

Focal Length

 Determines distance and width.

Short Focal Length (e.g., 4.5mm): Enables ultra-wide shots, similar to standing in a corner to see a whole room.

• Pros: Great for panoramas/meeting rooms. 
• Cons: Faces appear small; unsuitable for long distances.

Long Focal Length (e.g., 125mm–135mm): Enables telephoto shots, similar to using binoculars.

• Pros: Magnifies distant subjects clearly. 
• Cons: Narrow FOV; only shows a small center area.

Note: Tracking requires a balance. Too much wide-angle makes targets too small; too much telephoto makes it easy for targets to move out of frame.

Aperture 

Determines light intake.

• Lower F-number (e.g., F1.8): More light enters; clearer images in the dark.
• Higher F-number (e.g., F4.0): Less light; prone to noise in low light.

AI needs clean images for analysis. For indoor use, a large aperture (F1.8–F2.0) is preferred. Zoom Lens (e.g., 4.5mm to 135mm): Allows motorized zooming. It shifts to wide-angle when a target is close and zooms in when it is far, allowing the AI to adjust the frame dynamically.

Selecting the Image Sensor

The sensor is the camera’s "retina". It is the critical component for image quality, night vision, and motion performance.

Sensor Size

Larger sensors (e.g., 1/1.8") receive more light, offer better low-light performance, and provide a shallower depth of field for a more "three-dimensional" look. 1/2.8" or 1/1.8" are common sizes that balance cost and performance.

Resolution

 (e.g., 1080p, 4K). Higher resolution allows the AI to crop or enlarge a target while maintaining detail. While 1080p is sufficient for classrooms, 4K is advantageous for large venues or stadiums.

Pixel Size & Low Light

In two sensors with the same resolution, the larger physical sensor has larger pixels, resulting in less noise. Since AI tracking often fails on grainy images, prioritize low-light performance over raw pixel count in dim settings.

Frame Rate (fps)

 Higher frame rates reduce motion blur, making it easier for AI to predict movement trajectories.

• 30fps: Sufficient for general office or classroom tracking.
• 60fps: Best for high-speed sports or fast-moving subjects.

Optical Zoom vs. Digital Zoom

Optical zoom achieves true magnification by physically adjusting the lens elements to enlarge the image while maintaining full resolution. In contrast, digital zoom simply crops and enlarges a portion of the original frame. Common optical zoom factors include 3x, 5x, 10x, and 20x; for example, a 4-40mm lens offers a 10x optical zoom (40÷4=10). For AI auto-tracking cameras, when a target is distant, the AI can use optical zoom to bring the subject closer, ensuring that faces remain sharp and identifiable.

Conversely, digital zoom crops the original image and uses interpolation to fill in pixels, resulting in increased blurriness and noise as magnification increases. For AI systems, excessive digital zoom often results in a loss of detail that makes recognition difficult. Therefore, to achieve high-quality simultaneous tracking and zooming, an AI auto-tracking camera must be equipped with sufficient optical zoom capability.

Field of View (FOV) Planning

FOV is the "angle" of the eye's opening. It comprises horizontal FOV (HFOV) and Vertical FOV (VFOV). It is determined by focal length, sensor size, and installation height/distance.

Effective FOV planning for an AI auto-tracking camera requires several key considerations. First, you must define your boundaries: What is the widest field of view required during tracking, and what is the furthest target that must be captured?

• Scenario-Based Planning: In a classroom, the camera should encompass both the whiteboard and the podium. On a basketball court, it must cover either half or the full court.
• Installation Strategy: Determine the mounting location. Which wall will the camera be installed on?
• Distance and Focal Length: The distance between the camera and the target is critical. By combining the desired tracking range, mounting location, and distance, you can calculate the required focal length:
• For a wide-angle FOV, select a short focal length (e.g., 2.8–4mm).
• To capture clear facial details at a distance, opt for a camera with 20x or 30x optical zoom (e.g., 4.5–135mm).

Finally, evaluate the coverage of a single unit. In large indoor venues where one camera cannot cover the entire area, you must plan for a multi-camera setup combined with AI-driven auto-switching to ensure seamless tracking across the entire space.

Example of FOV Planning for AI Auto-Tracking Cameras: Lecturer Tracking in a Classroom

The following is an example of Field of View (FOV) planning for an AI auto-tracking camera.

Scenario Assumptions:

• Room Dimensions: 8 meters (deep) x 6 meters (wide).
• Installation: Centered on the rear wall at a height of 2.5 meters.

Operational Requirements:

• A panoramic view of the entire podium area is required.
• The ability to zoom in for a mid-shot (waist-up) of the lecturer is required.

Recommended Hardware Specifications: Based on the requirements above, the selected image sensor and lens specifications are as follows:

• Image Sensor: 1/2.8" or 1/1.8" CMOS sensor.
• Lens Focal Length: A zoom range covering approximately 3mm to 125mm.
• Wide End (3mm): Captures the entire podium and whiteboard.
• Telephoto End (52mm – 125mm): Captures mid-shots and close-ups of the lecturer.
• Optical Zoom: At least 20x optical zoom is recommended to ensure sufficient flexibility.
• Aperture: F1.8 – F2.0, optimized for indoor lighting conditions.

Tracking Logic: Once the FOV is configured according to this plan, the camera ensures seamless tracking: while the lecturer is moving, the camera utilizes the wide-angle view to prevent the subject from leaving the frame. When the lecturer stops to speak, the AI automatically zooms in to focus the shot on the lecturer.