A Diverse Low Cost High Performance Platform for Advanced Driver Assistance System (ADAS) Applications

Advanced driver assistance systems (ADAS) are becoming more and more popular. Lot of the ADAS applications such as Lane departure warning (LDW), Forward Collision Warning (FCW), Automatic Cruise Control (ACC), Auto Emergency Braking (AEB), Surround View (SV) that were present only in high-end cars in the past have trickled down to the low and mid end vehicles. Lot of these applications are also mandated by safety authorities such as EUNCAP and NHTSA. In order to make these applications affordable in the low and mid end vehicles, it is important to have a cost effective, yet high performance and low power solution. Texas Instruments (TI's) TDA3x is an ideal platform which addresses these needs. This paper illustrates mapping of different algorithms such as SV, LDW, Object detection (OD), Structure From Motion (SFM) and Camera-Monitor Systems (CMS) to the TDA3x device, thereby demonstrating its compute capabilities. We also share the performance for these embedded vision applications, showing that TDA3x is an excellent high performance device for ADAS applications.

[1]  Tom Flanagan,et al.  Empowering automotive vision with TI's Vision AccelerationPac , 2013 .

[2]  Manu Mathew,et al.  High Performance Front Camera ADAS Applications on TI's TDA3X Platform , 2015, 2015 IEEE 22nd International Conference on High Performance Computing (HiPC).

[3]  Pramod Swami,et al.  A robust and real-time image based lane departure warning system , 2016, 2016 IEEE International Conference on Consumer Electronics (ICCE).

[4]  Peter F. Sturm,et al.  A Factorization Based Algorithm for Multi-Image Projective Structure and Motion , 1996, ECCV.

[5]  Kumar Desappan,et al.  ORB in 5 ms: An Efficient SIMD Friendly Implementation , 2014, ACCV Workshops.

[6]  Paul A. Viola,et al.  Fast and Robust Classification using Asymmetric AdaBoost and a Detector Cascade , 2001, NIPS.

[7]  Niraj Nandan,et al.  Flexible Wide Dynamic Range (WDR) processing support in image signal processor (ISP) , 2015, 2015 IEEE International Conference on Consumer Electronics (ICCE).

[8]  Takeo Kanade,et al.  An Iterative Image Registration Technique with an Application to Stereo Vision , 1981, IJCAI.

[9]  Bill Triggs,et al.  Histograms of oriented gradients for human detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[10]  Soyeb Nagori,et al.  A fast color constancy scheme for automobile video cameras , 2014, 2014 International Conference on Signal Processing and Communications (SPCOM).

[11]  Aziz Umit Batur,et al.  Trends in camera based Automotive Driver Assistance Systems (ADAS) , 2014, 2014 IEEE 57th International Midwest Symposium on Circuits and Systems (MWSCAS).

[12]  Margrit Gelautz,et al.  Advances in Embedded Computer Vision , 2014, Advances in Computer Vision and Pattern Recognition.

[13]  Bernhard P. Wrobel,et al.  Multiple View Geometry in Computer Vision , 2001 .

[14]  Yucheng Liu,et al.  A Surround View Camera Solution for Embedded Systems , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops.