Human following by quadruped robots is a coupled perception–control problem in which detection availability, identity continuity, ranging reliability, and latency jointly determine behavior. This study experimentally evaluates a camera-based human-following pipeline on Boston Dynamics Spot. The final RGB-only follow loop combines YOLOv8n person-detection, DeepSORT tracking, monocular geometric ranging from bounding-box width, and bounded linear/yaw velocity control; spot depth was evaluated only as an alternative range source. YOLOv8n achieved 59.0% frame-level detection success indoors (36/61; 95% CI 46.5–70.5%) at 113.7 ms mean inference latency, and 38.75% outdoors (31/80; 95% CI 28.8–49.7%) at 118.1 ms. DeepSORT produced zero observed ID switches and fragmentations in 51 indoor and 45 outdoor multi-person frames, at about 3.2 FPS. On 12 outdoor frames with field-reference distances, geometric ranging yielded MAE 0.264 m and RMSE 0.323 m; spot depth was valid in only three frames. Continuous velocity control provided qualitatively smoother following than discrete commands and stopped on target loss. The study contributes a reproducible system-level analysis of practical design trade-offs and failure modes in camera-based human following by a commercial quadruped robot.