Path: EDN Asia >> Design Centre >> Automotive >> Future cars as mobile supercomputers
Automotive Share print

Future cars as mobile supercomputers

12 Oct 2015  | Klaus Neuenhuskes

Share this page with your friends

To answer demands to handle an increasing number of camera feeds for vision-based driver-assistance systems with image-recognition capabilities, Toshiba has developed an image-recognition processor family specifically for automotive applications. The architecture comprises high-performance Media-Processing Engines (MPEs), dedicated camera inputs and an array of hardware acceleration blocks. The current fourth-generation TMPV7608XBG processor family integrates up to eight MPE units with up to eight camera inputs and multiple hardware accelerators optimised for functions such as pixel calculation and filtering, enhanced affine transforms for distortion reduction and image sizing, and functions for histogram manipulation and matching. These hardware accelerators incorporate the latest and most advanced techniques, to deliver even faster performance than processors from previous generations (figure 1).


Figure 1: Media-Processing Engines and dedicated hardware accelerators ensure high-performing yet power-efficient processing.


Automotive-specific algorithms
In addition, Toshiba has implemented proprietary processing algorithms such as its CoHOG (Co-occurrence Histograms of Oriented Gradients), enhanced CoHOG and Structure from Motion (SfM) functions in dedicated hardware. With these enhancements, this fourth-generation processor delivers ten times greater performance than the previous generation of processors featuring four MPE units.

Toshiba created its CoHOG technology to enhance detection of human beings in various situations such as walking, cycling, sitting, or people in wheelchairs. This is achieved by comparing processed detected data with known characteristics of human body shapes and movement. CoHOG looks for pairs of gradients within certain upper and lower limits to detect features such as shoulders, arms, legs or hips. Knowing also that the features will have a certain orientation relative to each other, within physiological limits such as maximum and minimum limb lengths, range of movement and overall height helps ensure correct identification. The technique can also be extended to allow detection of other objects such as animals.

More recently, Toshiba has also developed the enhanced CoHOG accelerator, which provides extremely high pedestrian-recognition accuracy during night-time by analysing colour-based gradients of images from multiple Full-HD cameras (figure 2).


Figure 2: Enhanced CoHOG enables night-time pedestrian detection.



 First Page Previous Page 1 • 2 • 3 Next Page Last Page


Want to more of this to be delivered to you for FREE?

Subscribe to EDN Asia alerts and receive the latest design ideas and product news in your inbox.

Got to make sure you're not a robot. Please enter the code displayed on the right.

Time to activate your subscription - it's easy!

We have sent an activate request to your registerd e-email. Simply click on the link to activate your subscription.

We're doing this to protect your privacy and ensure you successfully receive your e-mail alerts.


Add New Comment
Visitor (To avoid code verification, simply login or register with us. It is fast and free!)
*Verify code:
Tech Impact

Regional Roundup
Control this smart glass with the blink of an eye
K-Glass 2 detects users' eye movements to point the cursor to recognise computer icons or objects in the Internet, and uses winks for commands. The researchers call this interface the "i-Mouse."

GlobalFoundries extends grants to Singapore students
ARM, Tencent Games team up to improve mobile gaming


News | Products | Design Features | Regional Roundup | Tech Impact