Q1. What are the contributions in "Fuzzy color histogram-based video segmentation" ?
The authors present a fuzzy color histogram-based shot-boundary detection algorithm specialized for contentbased copy detection applications. The proposed method aims to detect both cuts and gradual transitions ( fade, dissolve ) effectively in videos where heavy transformations ( such as cam-cording, insertions of patterns, strong re-encoding ) occur.
Q2. What have the authors stated for future works in "Fuzzy color histogram-based video segmentation" ?
As a future work the authors will use the detected shot boundaries, masks of still regions, picture-in-picture window boundaries, and the fuzzy color histogram method in their content-based copy detection system.
Q3. How does the method determine whether there is a shot change?
By matching the same objects and scenes using contrast context histogram (CCH) in two adjacent frames, the method decides that there is no shot change.
Q4. What is the common approach for CBCD?
In the field of CBCD, representing video with a set of keyframes (one or more representative frame for each shot) is a common approach.
Q5. What is the definition of a fuzzy logic approach for detecting cut?
In , histogram differences of consecutive frames are characterized as fuzzy terms, such as small, significant and large, and fuzzy rules for detecting abrupt and gradual transitions are formulated in a fuzzy-logic-based framework for segmentation of video sequences.
Q6. How did the authors obtain the scale and offset information of all picture-in-picture transformations?
The authors obtained the scale and offset information of all picture-in-picture transformations by processing the groundtruth data used for generating query videos.
Q7. What is the basic idea of the keypoint matching-based shot-boundary detection methods?
iv Local keypoint matching (KM): Recognizing the objects and scenes throughout the video is the basic idea of the keypoint matching-based shot-boundary detection methods.
Q8. How many frames per second do Douze et al. extract?
Douze et al. prefer extracting 2.5 frames per second for query videos, and extracting only a few representative keyframes for the dataset .
Q9. What is the method for detecting shot-boundaries?
Their tests with 50 query videos, which represents each transformation type with at least 4 videos, showed that fuzzy color histogram-based shot-boundary detection method can achieve higher accuracy values, while reducing false alarms.
Q10. How does the fuzzy color histogram method work?
The authors propose a fuzzy color histogram-based shot-boundary detection method for the videos where heavy transformations (such as cam-cording, insertions of patterns, strong re-encoding) occur.
Q11. How does the fuzzy color histogram method achieve a lower false alarm rate?
Their method also achieves a lower false alarm rate with a precision of 93.67%, whereas the precision values of the other methods could only reach up to 53.21%.
Q12. What is the effect of a mask for still regions?
Although the insertion of a pattern or text does not affect the shot-boundary detection process strongly, a mask for still regions, which includes the inserted pattern or text, will increase the effectiveness of a CBCD system.