Workshopvin4 Region Of Interest Advanced Video Coding

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Workshopvin4 Region Of Interest Advanced Video Coding

  1. 1. Region-of-Interest Advanced Video Coding IMEC Inventor: Jiangbo Lu Presenter: Gauthier Lafruit
  2. 2. RoI-AVC = Region-of-Interest Advanced Video Coding For stationary camera video applications: (e.g., video conference, video surveillance, news broadcast) • Foreground moving objects of crucial interest RoI for smart video processing • RoiAVC straddling computer vision & video coding a joint optimized design • Battery powered cameras for low bandwidth scenarios encoding efficiency & complexity crucial Frame-based Object -based RoiAVC RoI-based A practical semantic video codec with the coding efficiency and complexity advantages over state-of-art H.264/AVC Striking a sweet spot between frame-based video coding paradigm and object-based video coding paradigm Powered by our key competence in fast reliable RoI detection and coding schemes 2
  3. 3. Outline: RoI-AVC framework and strength A joint optimized design bridging the two worlds Vision world Video world Multi-scale motion RoI bounding - H.264 video H.264 video RoI detection box generation encoder decoder Metadata of Bounding-boxes Previous frame Current frame Reconstructed frame • Avoiding the initial background • Up to 34% bit-rate saving @ training and online updating similar quality over H.264/AVC • Reliable motion RoI detection • 2.x to 3.x faster (including RoI • 20 fps @ 352x288 w/o manual overhead) than H.264 reference optimization on Intel Pentium 4 encoder, similar for the decoder 3 To appear in IEEE ICASSP 2007
  4. 4. Vision world: multi-scale motion RoI detection Multi-scale motion RoI detection Previous frame Pixel- Pixel - level Region- Region-level processing processing Detected motion RoI Current frame Multi-scale motion RoI detection Multi-scale structural change aggregation as the key contribution An integrated fast and reliable motion RoI detection approach Directly applied to two successive video frames w/o a BG model Robust to flicking lighting and camera noise, and less sensitive to the thresholds 4
  5. 5. Multi-scale motion RoI detection: flowchart Region- Region-level processing Pixel- Pixel-level processing Median filter Multi-scale decomp . Multi-scale structural change aggregation Laplacian operator Bounding-box Morphological closing generation & extending Fast motion pixel Size-based noisy clustering changes culling Optimized connected component analysis 5
  6. 6. Video world: flexible MB-based H.264/AVC coding Flexible MB-based H.264/AVC codec Flexible MB-based Flexible MB-based H.264 encoder H.264 decoder Detected motion RoI Reconstructed frame Metadata of Bounding-boxes MB-based RoI coding Flexible organization of MBs 16 17 18 Flexible MB-based codec: 1 2 3 19 20 21 1 2 3 4 Largely reduced coding bit-rate and 4 5 6 22 23 24 5 6 7 8 7 8 9 9 10 11 12 complexity 10 11 12 13 14 15 13 14 15 16 21 22 17 18 19 20 23 24 Data locality-preserving ordering 25 26 27 28 w/o changing MB-based pipeline m MB of 1st Motion RoI n MB of 2 nd Motion RoI MB of background Could be fully compliant to AVC 6
  7. 7. Compared to the prior methods from different worlds Video world Current input frame Results of [CSVT’01] Results of [MM’01] Our results Vision world Current input frame Gaussian hypothesis test The single-scale variant Our multi-scale scheme 7
  8. 8. Video demo 1: multi-scale motion RoI detection Ballet @ 1024 x 768 from MSR camera-4 Detected motion blobs Bounding-boxes superimposed upon the original frames 8
  9. 9. Video demo 2: perceptual quality of RoI-AVC Indoor monitoring News broadcast Original video sequences Reconstructed video sequences 9

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