Title | ||
---|---|---|
A Diverse Low Cost High Performance Platform for Advanced Driver Assistance System (ADAS) Applications. |
Abstract | ||
---|---|---|
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. |
Year | DOI | Venue |
---|---|---|
2016 | 10.1109/CVPRW.2016.107 | IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops |
Field | DocType | Volume |
Structure from motion,Computer vision,Object detection,Advanced driver,Lane departure warning system,Cruise control,Computer science,Advanced driver assistance systems,Real-time computing,Collision,Artificial intelligence,Embedded system | Conference | 2016 |
Issue | ISSN | Citations |
1 | 2160-7508 | 1 |
PageRank | References | Authors |
0.35 | 3 | 15 |
Name | Order | Citations | PageRank |
---|---|---|---|
Prashanth Viswanath | 1 | 4 | 2.10 |
Kedar Chitnis | 2 | 17 | 3.69 |
Pramod Swami | 3 | 8 | 2.56 |
Mihir Mody | 4 | 43 | 10.93 |
Sujith Shivalingappa | 5 | 1 | 0.69 |
Soyeb Nagori | 6 | 10 | 2.67 |
Manu Mathew | 7 | 5 | 3.18 |
Kumar Desappan | 8 | 8 | 1.88 |
Shyam Jagannathan | 9 | 1 | 1.37 |
Deepak Poddar | 10 | 1 | 1.03 |
Anshu Jain | 11 | 4 | 1.09 |
H. Garud | 12 | 75 | 4.14 |
Vikram V. Appia | 13 | 41 | 3.98 |
Mayank Mangla | 14 | 1 | 0.35 |
shashank dabral | 15 | 7 | 1.63 |