Target tracking with dynamically adaptive correlation

• Dynamically adaptive correlation is used for robust target tracking.
• Proposed algorithm does not require an offline training process.
• Prediction and re-detection mechanisms are used to increase tracking efficiency.
• Dynamically-adaptive filtering is robust to noise, clutter and illumination.
• Algorithm outperforms well-known trackers in terms of objective metrics.

A reliable algorithm for target tracking based on dynamically adaptive correlation filtering is presented. The algorithm is capable of tracking with high accuracy the location of a target in an input video sequence without using an offline training process. The target is selected at the beginning of the algorithm. Afterwards, a composite correlation filter optimized for distortion tolerant pattern recognition is designed to recognize the target in the next frame. The filter is dynamically adapted to each frame using information of current and past scene observations. Results obtained with the proposed algorithm in synthetic and real-life video sequences, are analyzed and compared with those obtained with recent state-of-the-art tracking algorithms in terms of objective metrics.