Detect moving objects in videos
Control object motion in videos using 2D trajectories
Watch and analyze videos with object detection
Product Prototype 1
A UI for drone detection for YOLO-powered detection system.
Identify objects in images and videos
Track points in a video by clicking or using grid
Identify objects in live video
Detect objects in uploaded videos or live streams
Paligemma2 Detection with Supervision
Automated Insect Detection
Detect objects in a video stream
Process videos to detect and track objects
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.