Detect moving objects in videos
YOLOv11n & DeepSeek 1.5B LLM—Running Locally
Track and count vehicles in real-time
Track and count objects in videos
Detect objects in a video stream
Detect objects in real-time video streams
A UI for drone detection for YOLO-powered detection system.
Process videos to detect and track objects
Detect objects in real-time from webcam video
Detect objects in images or videos
Find objects in videos
Detect cars, trucks, buses, and motorcycles in videos
Efficient Track Anything
Motion detection in videos using OpenCV is a technique to identify and track moving objects within video frames. OpenCV provides robust libraries and tools to process video streams, enabling real-time detection of motion. This is achieved by analyzing consecutive frames and detecting differences, which indicate movement. It is widely used in surveillance, traffic monitoring, and object tracking applications.
cv2.VideoCapture().cv2.createBackgroundSubtractorMOG2() to subtract background and detect moving objects.cv2.threshold() to refine detection.cv2.findContours() and cv2.drawContours().cv2.imshow().cv2.destroyAllWindows().What causes latency in motion detection?
Latency can be caused by high-resolution video processing, inefficient code, or hardware limitations.
How can I reduce false positives?
Adjust the sensitivity of the background subtractor and apply morphological operations to refine detection.
Why does the detector struggle in changing light conditions?
Variations in lighting can affect background subtraction. Use adaptive algorithms or pre-processing techniques to stabilize frames.