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Automatic Caption Localization in Compressed Video By Yu Zhong, Hongjiang Zhang, and Anil K. Jain, Fellow, IEEE IEEE Transactions on Pattern Analysis and.

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Presentation on theme: "Automatic Caption Localization in Compressed Video By Yu Zhong, Hongjiang Zhang, and Anil K. Jain, Fellow, IEEE IEEE Transactions on Pattern Analysis and."— Presentation transcript:

1 Automatic Caption Localization in Compressed Video By Yu Zhong, Hongjiang Zhang, and Anil K. Jain, Fellow, IEEE IEEE Transactions on Pattern Analysis and Machine Intelligence Vol 22, No. 4, April 2000

2 Introduction Caption text on video General methods for caption extraction Proposed Method How it works Evaluation

3 Caption Text on Video Parse, index and abstract of Video Caption Text Information of Video Describe the content Catch “highlights”

4 General Extraction Methods Component-based Geometrical arrangement Homogeneous color Texture-based Contrast the background Horizontal intensity variation

5 Most published method Applied on uncompressed images Digital video and images Compressed (MPEG & JPEG) DCT (Discrete Cosine Transform) coding Reducing interframe redundancy (for MPEG)

6 Proposed Method Step 1 & 2 Detecting Blocks Step 3 Refinement Step 4 Segmentation of rows Step 1 Step 2 Step 3 Step 4

7 Proposed Method Source frame

8 Step 1 & 2 Detecting Blocks of High Horizontal Spatial Intensity Variation Operates in DCT domain Not necessary to decompress Unit: 8x8 blocks in I-frames (Intracoded) Quantized DCT coefficients Readily extracted Fast DCT blocks with high horizontal intensity variation

9 Step 3 Remove noise by applying Morphological Operations Step 1 & 2 Picked high contrast nontext blocks Disconnected text blocks Wide spacing, low contrast, large fonts Step 3 Remove most isolated blocks Merges nearby blocks Applying Morphological Operations

10 Step 4 Segmentation based on vertical intensity variation Detected text regions Large vertical intensity variation Local vertical harmonics Corresponding row of text High vertical spectrum energy After horizontal/vertical text energy test

11 Dilating the previous result by one block

12 Evaluation Not work properly when: Very big characters Too widely spaced text Image texture

13 Caption Text on Video Parse, index and abstract of Video Caption Text Information of Video Describe the content Catch “highlights”

14 Evaluation Commonly used caption NOT very big characters NOT too widely spaced text NOT image texture Therefore, important information retrieved!

15 Evaluation Future work Proposed to other transform-based compressions Use also color information to improve accuracy Combining DCT blocks to support larger fonts Solution to P- and B-frames

16 Summary Proposed caption localization method For compressed video Fast Further development is needed to improve: Accuracy Support other compression methods


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