License plate recognition (LPR) system is to help alert relevant personnel of any passing vehicle in the surveillance area.
In order to test algorithms for license plate recognition, it is necessary to have input frames in which the ground truth is
determined. The purpose of ground truth data is here to provide an absolute reference for performance evaluation or
training purposes. However, annotating ground truth data for real-life inputs is very disturbing task because of timeconsuming
manual. In this paper, we proposed a method of semi-automatic ground truth generation for license plate
recognition in video sequences. The method started from region of interesting detection to rapidly extract characters lines
followed by a license plate recognition system to verify the license plate regions and recognized the numbers. On the top
of the LPR system, we incorporated a tracking-validation mechanism to detect the time interval of passing vehicles in
input sequences. The tracking mechanism is initialized by a single license plate region in one frame. Moreover, in order
to tolerate the variation of the license plate appearances in the input sequences, the validator would be updated by
capturing positive and negatives samples during tracking. Experimental results show that the proposed method can
achieve promising results.
Automatic authoring of MTV-style home video using music tempo and visual tempo analysis is investigated in this research. The music tempo is extracted using the onset analysis. The frame-level visual tempo is detected based on the motion degree between consecutive frames. The object-level visual tempo is performed based on the tension analysis of facial expression. Finally, the authoring methodology is presented, which consists of music and visual tempo matching to product MTV-Style video. Experiment results using baby home video are given to demonstrate the performance of the proposed algorithm.