G. Valenzise *, M. Tagliasacchi *, S. Tubaro *, L. Piccarreta Picture Coding Symposium 2007 November 7-9, 2007 – Lisboa, Portugal * Dipartimento di Elettronica e Informazione, Politecnico di Milano
A -domain Rate Controller for Multiplexed Video Sequences PCS 2007, November 7, 2007 Transmit multiple video streams over a shared channel ◦ Broadcast television ◦ Video-surveillance ◦ etc… The channel bandwidth is limited Equal bandwidth partitioning is not optimal
A -domain Rate Controller for Multiplexed Video Sequences PCS 2007, November 7, 2007 Find an optimal way to allocate channel bandwidth among sequences Example: two video sequences time quality time quality time quality
A -domain Rate Controller for Multiplexed Video Sequences PCS 2007, November 7, 2007 Formulate the MINAVE and MINVAR problems in the -domain Assumptions: ◦ Constant bit rate (CBR) channel ◦ Frame-by-frame optimization Find a closed form solution for the MINVAR Compare the MINAVE and MINVAR criteria ◦ Check the coding efficiency loss for the average distortion Relax the CBR assumption ◦ Temporal smoothing
A -domain Rate Controller for Multiplexed Video Sequences PCS 2007, November 7, 2007 Rate-distortion operational curve of each frame can be described in the ρ-domain (He and Mitra, 2002): ρ-domain parameters can be estimated from decoded sequences
A -domain Rate Controller for Multiplexed Video Sequences PCS 2007, November 7, 2007 (He and Mitra, 2002)
A -domain Rate Controller for Multiplexed Video Sequences PCS 2007, November 7, 2007 Which is equivalent to solving When
A -domain Rate Controller for Multiplexed Video Sequences PCS 2007, November 7, 2007 MINAVE MINVAR
A -domain Rate Controller for Multiplexed Video Sequences PCS 2007, November 7, 2007 Average distortion of MINAVE Average distortion of MINVAR We know (by definition!) QUESTION: ◦ What is the coding efficiency loss?
A -domain Rate Controller for Multiplexed Video Sequences PCS 2007, November 7, 2007 Example: ◦ 3 video sequences to be multiplexed on a shared channel ◦ Total rate: R = 1.2 bpp ◦ For each frame we allocate the available bandwidth according to either the MINAVE or the MINVAR criteria ◦ We can evaluate then the resulting average distortion using the exponential -domain model
A -domain Rate Controller for Multiplexed Video Sequences PCS 2007, November 7, 2007
A -domain Rate Controller for Multiplexed Video Sequences PCS 2007, November 7, 2007 Average distortion of MINAVE Average distortion of MINVAR The coding efficiency loss is
A -domain Rate Controller for Multiplexed Video Sequences PCS 2007, November 7, 2007 Simulations: ◦ Extract the -domain parameters from 3 real sequences ◦ Compute the MINAVE and MINVAR rates for each sequences, for each frame ◦ Compute the coding efficiency loss
A -domain Rate Controller for Multiplexed Video Sequences PCS 2007, November 7, 2007
A -domain Rate Controller for Multiplexed Video Sequences PCS 2007, November 7, 2007
A -domain Rate Controller for Multiplexed Video Sequences PCS 2007, November 7, 2007
A -domain Rate Controller for Multiplexed Video Sequences PCS 2007, November 7, 2007 From Information Theory we know that Bad news.... But we can find a more stringent bound We need to find this term
A -domain Rate Controller for Multiplexed Video Sequences PCS 2007, November 7, 2007
A -domain Rate Controller for Multiplexed Video Sequences PCS 2007, November 7, 2007
A -domain Rate Controller for Multiplexed Video Sequences PCS 2007, November 7, 2007 Relax the CBR assumption ◦ Introduce a shared encoder buffer to perform VBR encoding We apply the MINVAR rate allocation while at the same time achieving temporal smoothing For each time instant: 1.Compute the CBR distortion profile 2.Smooth it with the low-pass filter (He, Zen and Chen, 2005) 3.Set D smooth as the target distortion and compute rates R i Relax or tighten the rate constraint according to the current buffer level
A -domain Rate Controller for Multiplexed Video Sequences PCS 2007, November 7, 2007 Temporal smoothness is achieved by means of a shared encoder buffer Target distortion level ◦ obtained solving MINVAR and CBR constraint C (He et al., 2005) Bits addedBits drained
A -domain Rate Controller for Multiplexed Video Sequences PCS 2007, November 7, 2007 Let If B res < 0 ◦ solve unconstrained minimization problem Else, if B res > 0 ◦ Solve constrained minimization problem with new rate constraint
A -domain Rate Controller for Multiplexed Video Sequences PCS 2007, November 7, 2007
A -domain Rate Controller for Multiplexed Video Sequences PCS 2007, November 7, 2007 H.264 decoder H.264 decoder H.264 decoder... H.264 bitstream Rate controller H.264 encoder H.264 encoder H.264 encoder BUFFER
A -domain Rate Controller for Multiplexed Video Sequences PCS 2007, November 7, 2007 MINAVE MINVAR smoothed MINVAR
A -domain Rate Controller for Multiplexed Video Sequences PCS 2007, November 7, 2007 MINAVE MINVAR smoothed MINVAR
A -domain Rate Controller for Multiplexed Video Sequences PCS 2007, November 7, 2007 F = Foreman H = Hall Monitor S = Soccer C = Coastguard
A -domain Rate Controller for Multiplexed Video Sequences PCS 2007, November 7, 2007 Summary: ◦ Proposed a MINVAR bit allocation for multiplexed video sequences ◦ The MINVAR allocation leverages on the -domain model (but works on any exponential model, i.e. at high rates) ◦ The coding efficiency loss w.r.t. MINAVE is, on average, of 0.5 dB Future work: ◦ Apply the MINVAR approach to Scalable Video Coding solve a discrete optimization problem…
A -domain Rate Controller for Multiplexed Video Sequences PCS 2007, November 7, 2007 Z. He and S. K. Mitra, “Optimum bit allocation and accurate rate control for video coding via -domain source modeling,” IEEE Trans. Circuits Syst. Video Technol., vol. 12, pp. 840– 849, November Z. He, W. Zeng, and C.W. Chen, “Low-pass filtering of rate-distortion functions for quality smoothing in real-time video communication,” IEEE Trans. Circuits Syst. Video Technol., vol. 15, no. 8, pp. 973–981, 2005.
A -domain Rate Controller for Multiplexed Video Sequences PCS 2007, November 7, 2007 Questions?