Automated Media Content Placement via Corner Tracking

The patent replaces the manual mechanical operation of frame-by-frame media content placement with an automated computer vision system. The system uses a pre-trained model with corner tracking technology to automatically identify target regions in video frames and place media content without human intervention, thereby dramatically improving placement efficiency while maintaining high accuracy through automated detection and positioning mechanisms.

The patent employs a pre-trained model that has been copied and trained on extensive video data to automatically detect target corners and regions. This trained model serves as a reusable template that can accurately identify placement regions across different videos without manual intervention, ensuring consistent high accuracy in media content placement by leveraging the patterns learned during the training phase.

The patent applies preliminary action by pre-training the model offline before deployment. The corner tracking model is trained in advance on large datasets to learn video frame characteristics and placement region patterns. Once trained, the model can be directly applied to new videos without requiring complex real-time training mechanisms, thus improving placement efficiency while keeping the deployed system relatively simple.