In recent years, CCTV footage has been integrated in systems to observe areas and detect traversing malicious actors (e.g., criminals, terrorists). However, this footage has "blind spots", areas where objects are detected with lower confidence due to their angle/distance from the camera. In this talk, we investigate a novel side effect of object detection in CCTV footage; location-based confidence weakness. We demonstrate that a pedestrian's position (distance, angle, height) in footage impacts an object detector's confidence. We analyze this phenomenon in four lighting conditions (lab, morning, afternoon, night) using five object detectors (YOLOv3, Faster R-CNN, SSD, DiffusionDet, RTMDet). We then demonstrate this in footage of pedestrian traffic from three locations (Broadway, Shibuya Crossing, Castro Street), showing they contain "blind spots" where pedestrians are detected with low confidence. This persists across various locations, object detectors, and times of day.