a novel multiresolution spatiotemporal saliency detection model and its applications in image and...
Post on 19-Dec-2015
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TRANSCRIPT
- Slide 1
- A Novel Multiresolution Spatiotemporal Saliency Detection Model and Its Applications in Image and Video Compression Chenlei Guo Liming Zhang Image Processing 2010
- Slide 2
- Outline Introduction Phase Spectrum of Quaternion Fourier Transform (PQFT) Detect Proto-Objects in the Spatiotemporal Saliency Map Hierarchical Selectivity (HS) Experiment Result Applications in Image and Video Coding Conclusions and Discussions
- Slide 3
- Introduction Most traditional object detectors need training Graph-based visual saliency detection can be very powerful but it demands a very high computational cost Most of the models only consider static images
- Slide 4
- Phase Spectrum of Quaternion Fourier Transform(PQFT) (1/3) Locations with less periodicity or less homogeneity create pop out proto objects in the reconstruction of the images phase spectrum An early saliency detection model : PFT
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- Quaternion Representation (2/3) Define the input image captured at time t as F(t) r(t), g(t), b(t) are color channels of F(t)
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- Calculate the Saliency Map By PQFT (3/3) 2-D gaussian filter
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- Detect Proto-Objects (1/3)
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- Alpha (2/3)
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- Gamma (3/3)
- Slide 10
- How PQFT Select Visual Resolution PQFT simulates the human vision system(HVS)
- Slide 11
- Hierarchical Selectivity Set hierarchical level
- Slide 12
- Experiment Results Video Sequence Natural Images Psychological Patterns
- Slide 13
- Video Sequence (1/3)
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- Video Sequence (2/3)
- Slide 15
- Video Sequence (3/3)
- Slide 16
- Natural Image
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- Evaluation Method - ROC True Positive Rate(TPR), False Positive Rate(FPR) Receiver Operating Characteristic (ROC) ROC curve = TPR/FPR ROC area = area beneath ROC curve The larger ROC area is, the better the prediction power of a saliency map.
- Slide 18
- Psychological Patterns (1/3)
- Slide 19
- Psychological Patterns (2/3)
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- Psychological Patterns (3/3)
- Slide 21
- Applications in Image and Video Coding Multiresolution Wavelet Domain Foveation Model (MWDF) Evaluate the performance of the HS-MWDF model in Image and video compression
- Slide 22
- Multiresolution Wavelet Domain Foveation Model (MWDF) JPEG 2000 has included the region-of-interest(RoI) coding in drafts A better way to find RoI:use Hierarchical Selectivity
- Slide 23
- Multiresolution Wavelet Domain Foveation Model (MWDF)
- Slide 24
- The Performance of HS-MWDF in Image Compression We use HS-MWDF model as a front end before standard compression (JPEG 2000) Set n fov => we only use the first n OCAs found by PQFT Auto fov => let the program itself decide the number
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- The Performance of HS-MWDF in Video Compression
- Slide 27
- Conclusion and Discussion Extend PFT model to PQFT model PQFT model is independent of parameters and prior knowledge, and is fast enough to meet real- time requirements Develop a model called HS-MWDF as a front end before the image/video encoder Problems: Cant deal with closure patterns well Only considers bottom-up information Insert the model into the image/video encoders
- Slide 28
- References