ffmpeg -i rtsp://cam1/stream -i rtsp://cam2/stream \ -i rtsp://cam3/stream -i rtsp://cam4/stream \ -filter_complex "xstack=inputs=4:layout=0_0|w0_0|0_h0|w0_h0" \ -f image2 pipe:1 Write a Python script that reads the mosaic frame and applies motion detection per quadrant.
for idx, (x1,y1,x2,y2) in enumerate(quadrants): cell_prev = prev_gray[y1:y2, x1:x2] cell_curr = gray[y1:y2, x1:x2] diff = cv2.absdiff(cell_prev, cell_curr) motion = np.sum(diff > 25) # Threshold of 25 if motion > (cell_w * cell_h * 0.01): # 1% of pixels changed print(f"MOTION detected in Camera idx+1") cv2.rectangle(frame, (x1,y1), (x2,y2), (0,0,255), 3) inurl multicameraframe mode motion work
As edge AI matures, you will find more URL endpoints like: http://camera/api/v2/multicamera?mode=tensorflow&track_id=person_001 Issue 2: The URL doesn't show "multicameraframe" but
Issue 1: "Motion work" fails because frames are out of sync Solution: Use PTP (Precision Time Protocol) or NTP to synchronize all cameras. Then use ffmpeg's -vsync cfr (constant frame rate) flag. Issue 2: The URL doesn't show "multicameraframe" but the feature exists Many manufacturers use different terms: multiview , nvr_layout , quad_split , or grid_view . Your inurl search should include synonyms. Issue 3: High latency between motion and alert Solution: Reduce the GOP (Group of Pictures) size on each camera to 15 or lower. Large GOPs delay decoding of motion frames. Conclusion: The Future of Unified Motion Frames The concept behind "inurl multicameraframe mode motion work" is evolving toward AI-driven multi-camera tracking . Modern systems don't just detect motion per camera cell—they track a person moving from Camera 1’s frame into Camera 2’s frame within the same mosaic. Large GOPs delay decoding of motion frames
ffprobe -v error http://192.168.1.101/video.cgi Look for URLs containing multicamera , frame , or motion - this is the inurl concept applied to your local network. Use FFmpeg’s xstack filter to combine 4 cameras into one frame: