MIPI CSI-2℠
CSI-2℠ Application for Vision
and Sensor Fusion Systems
Richard Sproul – Cadence
Design Systems, IP Architect
Overview
•  The expanding demand for imaging and vision based
systems in mobile, IoT and automotive products is
creating the need for multi-camera and sensor fusion
systems to look for novel ways to gather and process
multiple camera/sensor data streams whilst still fitting
into the mobile interface.
•  The presentation will highlight some of the key details
and requirements for a system with image processing
of a multi-camera/sensor system.
2
CSI-2 Application for Multi-Sensor Systems
Multi-Camera Applications
•  Imaging applications are everywhere
•  Mobile Phone
–  Selfie Picture in Picture
–  Gesture Recognition
•  Video Games
–  Gesture Recognition
•  Autonomous Driving
–  Pedestrian Detection
–  Signage Recognition
–  Night Vision
–  Parallel Parking!
•  In-Car Control
–  Gesture Recognition
4
More	than	the	
naked	eye…	
CSI-2 Application for Multi-Sensor Systems
Machine Vision
5
CSI-2 Application for Multi-Sensor Systems
Camera Applications
Op0mal	pathway	for	mul0ple	forward-looking	advancements	in	
imaging		
–	Key	Drivers:	Health,	Convenience,	Security,	Lifestyle,	Efficiency		
–	High-perf	pixel	conduit	needs	met	with	C/D-PHY	advancements		
–	Broad	defini0ons	and	fuzzy	range:	(i.e.	Wearable:	Near	Body,	On	
Body,	In	Body)		
•	Explore	possibili0es	of	overlap	between	Imaging	and	low-speed	
sensor	requirements	and	solu0ons		
Camera	Controller	Interface	(CCI/CCS)	
advancement	considera0ons:		
-	Point-to-Point	and	Mul0-Drop	configura0ons		
-	Energy	consumed	/	Gb	transfer		
-	Limit	latency	for	VB	&	HB		
-	Precision	Timing	&	Sync		
-	Independent	Transport:	Pixel	Data	&	Control		
-	Channel	Integrity	(Error	Detec0on)		
-	FW	Upload	(ISP,	Neural)
•  Options for physical interface
•  Pins, legacy, bandwidth
6
CSI-2 Application for Multi-Sensor Systems
MIPI CSI-2 Interfaces
•  Evolution of the CSI-2
7
CSI-2 Application for Multi-Sensor Systems
CSI-2 Generations
8
CSI-2 Application for Multi-Sensor Systems
CSI-2 Performance
•  CSI-2 packets V1.x to V2.0
9
LP	
LP	
LP	
LP	
Transi0on	between	packets	to	LP	state	for	PHY	data	lane	(100ns)	
Transi0on	between	packets	by	using	filler	pa_erns	
CSI-2 Application for Multi-Sensor Systems
CSI-2 Packet Structure
•  Improve the effective bandwidth
10
0	
20	
40	
60	
80	
100	
120	
1000	 1250	 1500	 1800	 2000	 2250	 2500	
Frame	Rate	fps	
Bit	Rate	(Mbps)	
CSI-2	Frame	Rate	Improvement	V1.x	to	V2.x	
1920x1080	RAW12	
FPS	(V1.x)	 FPF	(V2.x)	
CSI-2 Application for Multi-Sensor Systems
CSI-2 Packet Transmission
•  Automotive application for driver assistance
- External systems and for in-car control
• Objects	
• High	
resolu0on	
• Night	image	
and	IR		
• In-car	
gesture	
• People	
detec0on	
• Medium	
resolu0on	
• Road	signage	
• Medium	
resolu0on	
Parking	
assistance	
CSI2 Application for Multi-Sensor Systems
Advanced Driver-Assistance System
CSI-2 Application for Multi-Sensor Systems
•  Application in a Multi-Camera Platform
12
Automotive AV
Reference Subsystem
MIPI	
DPHY	
Audio	DSP	
$I	 $D	
System Interconnect
Image/Vision	
DSP	
DMA	 I-RAM	 D-RAM	
AXI2	
AHB	
UART	 I2C	
32b	APB	
Timer	I2S	 GPIO	
AHB2	
APB	
32b	AHB	
QSP
I	
Soun
dWir
e	
Audio	
USB	
2/3	
devic
e	
Ethe
rnet	
MAC	
On-Chip	
System	SRAM	
1300MT/s	
DDR3	
Controller	
DDR-PHY	
64b	DDR3	SODIMM	
SD	
SDIO	
eMM
C	
Displa
y	
Inm.	
BR	
PHY	
USB	
PHY	
Pixel	
2AXI	
Color	
Conver
t	
Video	
Scalar	
HDMI	
PHY	
Image/Vision	
DSP	
DMA	 I-RAM	 D-RAM	
MIPI	
CSI-2	
Rx	
MIPI	
CSI-2	
RX	
MIPI	
CSI-2	
Rx	
MIPI	
DPHY	
MIPI	
DPHY	
Sensor	DSP	
$I
13
CSI-2 Application for Multi-Sensor Systems
Sensors Everywhere
•  The data does not have to be images…
•  LiDAR
•  The resolution is low (IR RAW data, typically 64 pixels high, though much more
horizontally)
•  Range is limited. Typical LiDARs see well to about 70 metres.
•  Refresh rates tend to be slower, at around 10fps.
•  RADAR
•  Long range – cruise control, brake assist
•  Ultrasonic
•  Short-range parking assist
•  Self parking ☺
•  Protocol support with user-defined data to transfer the bytes
14
CSI-2 Application for Multi-Sensor Systems
CSI-2 for Sensors
CSI-2 Application for Multi-Sensor Systems
CSI-2 Example Video Frame
•  Bandwidth on CSI-2 V1.1 – 4 Lanes 6Gbps
•  So with our 30fps, we have 200M bit to use
•  3 HD camera RGB888 1920x1200x24=165.888M
•  Also adding 100ns gaps (150 bit clocks)
•  3 x(1920x24) +3x150 = 138240
•  Embedded data line with image processed data (clusters, edges)
16
CSI-2	TX	Controller	
Video	Buffer	
Centralized	ECU	for	
Infotainment	or	ADAS	
Pixel	
Pixel	
Data	
Data	
Sensor	DSP	
Sensor	DSP	
PCIe	
Sensor	
DSP	
I2S	
I2S	
I2S	
SoundWire	
eMMC	
Apps	
USB	
DSI	
DDR	
DPHY	
PCIe	
PHY	
USB	
PHY	
Sensor
Sensor
Video	EP	
Video	EP	
PPI	
PPI	
DPHY
DPHY
Pixel	
Pixel	
PHY	
Data	
Data	
CSI-2 domain
Video	Buffer	
Data	Buffer	
Data	Buffer	
I2S	
SoundWire	
Sensor	
DSP	
CSI-2	RX	
CTRL	
Vision	
DSP	
CSI-2	
Vision	
DSP	
CSI-2	
CSI-2 Application for Multi-Sensor Systems
CSI-2 Sensor Fusion Example
•  Sensor Fusion ADAS System Topology
•  Merge the data from image and other sensors
•  Pre-processing the inline data for the application
•  Image Processing and the Application
•  Application processing will need to perform the ADAS system and
sensor analysis
17
CSI2 Application for Multi-Sensor Systems
CSI-2 Sensor Fusion Example
18
CSI-2 Application for Multi-Sensor Systems
Filling the Channels
D PHY
(MCNN)
D-PHY
(MFEN)
Pixel
Processor/
Application
DP
DP
DN
DN
D PHY
(SCNN)
D-PHY
(SFEN)
Pixel Stream 0
PPI
PPI
D-PHY
(MFEN)
DP
DN
D-PHY
(SFEN)
PPI
Pixel Stream 1
Pixel Stream 2
Pixel Stream 3
Sensor
Processor/
Application
Pixel Stream 4
Pixel Stream 5
Pixel Stream 6
Pixel Stream 7
CSI-2 Host
Controller
PPI
PPI
PPI
D-PHY
(MFEN)
D-PHY
(SFEN)
DP
DN
CSI-2 Slave
Controller
PPI PPI
Sensor
Control
Sensor
Control
Sensor
Sensor
Sensor
Sensor
Sensor
DATA
DATA
DATA
DATA
DATA
DATA DATA
CSI-2 Slave
Controller
CSI-2 Host
Controller
19
CSI-2 Application for Multi-Sensor Systems
Physical Interface
CSI-2 Application for Multi-Sensor Systems
CSI-2 Example Video Frame
•  Bandwidth on CSI-2 V1.1 – 4 Lanes 6Gbps
–  Using LS/LE to keep synchronisation and sequence
–  Use the virtual channel to identify the sensor
–  Use the data types (RAW, RGB, YUV and user defined)
–  Use the short packet sync events
•  Functional safety considerations
•  DPHY BER, RX error detection
•  Packet header ECC
•  Payload CRC
•  SP sync sequences, counting values
21
CSI2 Application for Multi-Sensor Systems
Functional Safety In CSI2 ADAS
•  Pitfalls of interleaved streams
22
CSI-2 Application for Multi-Sensor Systems
CSI-2 Interleaving Data
23
CSI-2 Application for Multi-Sensor Systems
CSI-2 Interleaving
CSI-2 Beyond Mobile
24
CSI-2 Beyond Mobile
•  System architecture considerations for CNN
applications:
•  Assist
•  Co-pilot
•  Automated
•  Optimal platform arch for the CNN engines
•  Central processing (+SW dev, lacks scalability / modularity, cost
may not align w/ entry-level cars)
•  Distributed processing (plug-and-play, scalable, each camera unit
enhances capability, complex system)
•  AlgoEngine: CPU / GPU / DSP / FPGA
•  Overall risks and uncertainty:
•  Market, product, execution, timing, regulators, infrastructure
25
CSI-2 Beyond Mobile
•  What can technology do for us?
•  Imaging: digital photography vs. vision
•  Scene capture, object capture & track, modeling & measurement
•  Perception and decision-making using real-time
streaming image data:
•  Camera, RADAR, LiDAR, sonar (varying detection capabilities vs.
cost)
•  Performance vs robustness – consequence of error
•  Camera position, lighting, environmental factors, required accuracy
for object detection
26

MIPI DevCon 2016: MIPI CSI-2 Application for Vision and Sensor Fusion Systems

  • 1.
    MIPI CSI-2℠ CSI-2℠ Applicationfor Vision and Sensor Fusion Systems Richard Sproul – Cadence Design Systems, IP Architect
  • 2.
    Overview •  The expandingdemand for imaging and vision based systems in mobile, IoT and automotive products is creating the need for multi-camera and sensor fusion systems to look for novel ways to gather and process multiple camera/sensor data streams whilst still fitting into the mobile interface. •  The presentation will highlight some of the key details and requirements for a system with image processing of a multi-camera/sensor system. 2
  • 3.
    CSI-2 Application forMulti-Sensor Systems Multi-Camera Applications •  Imaging applications are everywhere •  Mobile Phone –  Selfie Picture in Picture –  Gesture Recognition •  Video Games –  Gesture Recognition •  Autonomous Driving –  Pedestrian Detection –  Signage Recognition –  Night Vision –  Parallel Parking! •  In-Car Control –  Gesture Recognition
  • 4.
    4 More than the naked eye… CSI-2 Application forMulti-Sensor Systems Machine Vision
  • 5.
    5 CSI-2 Application forMulti-Sensor Systems Camera Applications Op0mal pathway for mul0ple forward-looking advancements in imaging – Key Drivers: Health, Convenience, Security, Lifestyle, Efficiency – High-perf pixel conduit needs met with C/D-PHY advancements – Broad defini0ons and fuzzy range: (i.e. Wearable: Near Body, On Body, In Body) • Explore possibili0es of overlap between Imaging and low-speed sensor requirements and solu0ons Camera Controller Interface (CCI/CCS) advancement considera0ons: - Point-to-Point and Mul0-Drop configura0ons - Energy consumed / Gb transfer - Limit latency for VB & HB - Precision Timing & Sync - Independent Transport: Pixel Data & Control - Channel Integrity (Error Detec0on) - FW Upload (ISP, Neural)
  • 6.
    •  Options forphysical interface •  Pins, legacy, bandwidth 6 CSI-2 Application for Multi-Sensor Systems MIPI CSI-2 Interfaces
  • 7.
    •  Evolution ofthe CSI-2 7 CSI-2 Application for Multi-Sensor Systems CSI-2 Generations
  • 8.
    8 CSI-2 Application forMulti-Sensor Systems CSI-2 Performance
  • 9.
    •  CSI-2 packetsV1.x to V2.0 9 LP LP LP LP Transi0on between packets to LP state for PHY data lane (100ns) Transi0on between packets by using filler pa_erns CSI-2 Application for Multi-Sensor Systems CSI-2 Packet Structure
  • 10.
    •  Improve theeffective bandwidth 10 0 20 40 60 80 100 120 1000 1250 1500 1800 2000 2250 2500 Frame Rate fps Bit Rate (Mbps) CSI-2 Frame Rate Improvement V1.x to V2.x 1920x1080 RAW12 FPS (V1.x) FPF (V2.x) CSI-2 Application for Multi-Sensor Systems CSI-2 Packet Transmission
  • 11.
    •  Automotive applicationfor driver assistance - External systems and for in-car control • Objects • High resolu0on • Night image and IR • In-car gesture • People detec0on • Medium resolu0on • Road signage • Medium resolu0on Parking assistance CSI2 Application for Multi-Sensor Systems Advanced Driver-Assistance System
  • 12.
    CSI-2 Application forMulti-Sensor Systems •  Application in a Multi-Camera Platform 12 Automotive AV Reference Subsystem MIPI DPHY Audio DSP $I $D System Interconnect Image/Vision DSP DMA I-RAM D-RAM AXI2 AHB UART I2C 32b APB Timer I2S GPIO AHB2 APB 32b AHB QSP I Soun dWir e Audio USB 2/3 devic e Ethe rnet MAC On-Chip System SRAM 1300MT/s DDR3 Controller DDR-PHY 64b DDR3 SODIMM SD SDIO eMM C Displa y Inm. BR PHY USB PHY Pixel 2AXI Color Conver t Video Scalar HDMI PHY Image/Vision DSP DMA I-RAM D-RAM MIPI CSI-2 Rx MIPI CSI-2 RX MIPI CSI-2 Rx MIPI DPHY MIPI DPHY Sensor DSP $I
  • 13.
    13 CSI-2 Application forMulti-Sensor Systems Sensors Everywhere
  • 14.
    •  The datadoes not have to be images… •  LiDAR •  The resolution is low (IR RAW data, typically 64 pixels high, though much more horizontally) •  Range is limited. Typical LiDARs see well to about 70 metres. •  Refresh rates tend to be slower, at around 10fps. •  RADAR •  Long range – cruise control, brake assist •  Ultrasonic •  Short-range parking assist •  Self parking ☺ •  Protocol support with user-defined data to transfer the bytes 14 CSI-2 Application for Multi-Sensor Systems CSI-2 for Sensors
  • 15.
    CSI-2 Application forMulti-Sensor Systems CSI-2 Example Video Frame •  Bandwidth on CSI-2 V1.1 – 4 Lanes 6Gbps •  So with our 30fps, we have 200M bit to use •  3 HD camera RGB888 1920x1200x24=165.888M •  Also adding 100ns gaps (150 bit clocks) •  3 x(1920x24) +3x150 = 138240 •  Embedded data line with image processed data (clusters, edges)
  • 16.
  • 17.
    •  Image Processingand the Application •  Application processing will need to perform the ADAS system and sensor analysis 17 CSI2 Application for Multi-Sensor Systems CSI-2 Sensor Fusion Example
  • 18.
    18 CSI-2 Application forMulti-Sensor Systems Filling the Channels D PHY (MCNN) D-PHY (MFEN) Pixel Processor/ Application DP DP DN DN D PHY (SCNN) D-PHY (SFEN) Pixel Stream 0 PPI PPI D-PHY (MFEN) DP DN D-PHY (SFEN) PPI Pixel Stream 1 Pixel Stream 2 Pixel Stream 3 Sensor Processor/ Application Pixel Stream 4 Pixel Stream 5 Pixel Stream 6 Pixel Stream 7 CSI-2 Host Controller PPI PPI PPI D-PHY (MFEN) D-PHY (SFEN) DP DN CSI-2 Slave Controller PPI PPI Sensor Control Sensor Control Sensor Sensor Sensor Sensor Sensor DATA DATA DATA DATA DATA DATA DATA CSI-2 Slave Controller CSI-2 Host Controller
  • 19.
    19 CSI-2 Application forMulti-Sensor Systems Physical Interface
  • 20.
    CSI-2 Application forMulti-Sensor Systems CSI-2 Example Video Frame •  Bandwidth on CSI-2 V1.1 – 4 Lanes 6Gbps –  Using LS/LE to keep synchronisation and sequence –  Use the virtual channel to identify the sensor –  Use the data types (RAW, RGB, YUV and user defined) –  Use the short packet sync events
  • 21.
    •  Functional safetyconsiderations •  DPHY BER, RX error detection •  Packet header ECC •  Payload CRC •  SP sync sequences, counting values 21 CSI2 Application for Multi-Sensor Systems Functional Safety In CSI2 ADAS
  • 22.
    •  Pitfalls ofinterleaved streams 22 CSI-2 Application for Multi-Sensor Systems CSI-2 Interleaving Data
  • 23.
    23 CSI-2 Application forMulti-Sensor Systems CSI-2 Interleaving
  • 24.
  • 25.
    CSI-2 Beyond Mobile • System architecture considerations for CNN applications: •  Assist •  Co-pilot •  Automated •  Optimal platform arch for the CNN engines •  Central processing (+SW dev, lacks scalability / modularity, cost may not align w/ entry-level cars) •  Distributed processing (plug-and-play, scalable, each camera unit enhances capability, complex system) •  AlgoEngine: CPU / GPU / DSP / FPGA •  Overall risks and uncertainty: •  Market, product, execution, timing, regulators, infrastructure 25
  • 26.
    CSI-2 Beyond Mobile • What can technology do for us? •  Imaging: digital photography vs. vision •  Scene capture, object capture & track, modeling & measurement •  Perception and decision-making using real-time streaming image data: •  Camera, RADAR, LiDAR, sonar (varying detection capabilities vs. cost) •  Performance vs robustness – consequence of error •  Camera position, lighting, environmental factors, required accuracy for object detection 26