Real-Time Video in Mobile Telehealth Scenarios: Elastic Algorithms for Region of Interest Compression

1. Real-time Video in Mobile Telehealth – Scenario START • Mobile Expert • Video Client • Home • Hospital • Community Mobile Patient Future Scenario Sufficient bits for State 1? Sufficient bits for State 2? Sufficient bits for State 3? NO Wireless Network NO NO … YES YES YES {ML,ML} {ML,PL} {ML,DL} Medical Center Information Server ER-PICU Patient STOP … Elastic Algorithms for Region of Interest Video Compression, with Application to Mobile Telehealth Pilot Tests on Training Sequences Sira Rao and Dr. Nikil Jayant Multimedia Communications Lab School of Electrical and Computer Engineering Georgia Institute of Technology, Atlanta, GA Encoder State Machine Encoder State Table – Region-Quality Mappings Performance Results Detection of Transitions 600kbps 0.40 28.6 600kbps 0.19 25.2 State Transitions due to Inadequate Quality • Manual trigger of inadequate quality within the ROI • Automatic trigger through a PSNR difference method • Based on expectation of minimal difference in ROI and BKGRND quality • Offsets underestimation in nominal mappings • PSNR_TH state dependent i.e. expect higher differences where ROI and BKGRND have different quality abstractions (e.g. state 7 (PL ROI, BE BKGRND) and state 5 (PL ROI, PL BKGRND)) • Mapping from bits to quality levels may not always be satisfactorily achieved • Different medical features with likely different compression limits on PL, DL • Nominal mapping possibly the average value • Thus, when ROI not of PL or DL quality when current state indicates it to be so, transition to a lower state in the same row to increase R_ROI 900kbps 0.56 29.5 900kbps 0.29 27.7 600kbps 0.19 18.0 600kbps 0.36 20.4 900kbps 0.53 21.1 900kbps 0.29 18.8