Pilot Tests on Training Sequences

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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. - PowerPoint PPT Presentation

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Elastic Algorithms for Region of Interest Video Compression, with Application to Mobile Telehealth

Sira Rao and Dr. Nikil JayantMultimedia Communications Lab

School of Electrical and Computer EngineeringGeorgia Institute of Technology, Atlanta, GA

Pilot Tests on Training Sequences

Randomly Assigned

Video Sample Number

Bit Rate

(kbps)

Feature Sets Adequate to Assess?

Clinical Assessment

Rn1 100

Rib Retraction

Oral Cyanosis

Tripod Posture

1-5

1-5

1-5

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Rib Retraction

Oral Cyanosis

Tripod Posture

1-5

1-5

1-5

Comments

Comments

Comments

Rn10 1000

Rib Retraction

Oral Cyanosis

Tripod Posture

1-5

1-5

1-5

Comments

Comments

Comments

Encoder State Machine

Sufficient bits for State 1?

Sufficient bits for State 2?

Sufficient bits for State 3?

START

{ML,ML} {ML,PL} {ML,DL}

YES YES YES

NO NO NO

STOP

Encoder State Table – Region-Quality Mappings

ML PL DL BE

ML 1 2 3 4

PL 5 6 7

DL 8 9

BE 10

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

State Transitions due to Inadequate Quality

Real-time Video in Mobile Telehealth – Scenario

Wireless NetworkWireless Network

Mobile ExpertVideo ClientHomeHospitalCommunity

Mobile PatientFuture Scenario

ER-PICUPatient

Medical CenterInformation

Server

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))

0__

1__

___

FLAGQUALITYROI

else

FLAGQUALITYROI

THPSNRPSNRBKGRNDPSNRROIIf

Detection of Transitions600kbps

0.4028.6

600kbps0.1925.2

900kbps0.5629.5

900kbps0.2927.7

600kbps0.3620.4

600kbps0.1918.0

900kbps0.5321.1

900kbps0.2918.8

Quality Level ROI BKGRND

PL 0.3157 0.3157

DL 0.2104 0.2104

BE - 0.1052

BE_MIN - 0.0526

600 600 900 900 1200 1200

ROI BKGRND ROI BKGRND ROI BKGRND

Foreman 0.40 0.12 0.56 0.21 0.62 0.31

Flower 0.36 0.14 0.53 0.21 0.58 0.33

Football 0.38 0.13 0.55 0.21 0.62 0.31

MPEG2 0.19 0.19 0.29 0.29 0.39 0.39

Performance Results

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