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9 "ADAS" Solutions

1
Driver Drowsiness Detector
The logiDROWSINE is a computer vision IP core that detects driver drowsiness and distraction based on facial movements monitored through a camera placed in a vehicle cabin. The IP core monitors moveme...

2
Lane Marking Detector
The logiLMD Lane Marking Detection IP core from Xylon s logicBRICKS IP core library is designed to detect the lane markings on the roadway video scenarios captured from a rear-view camera, and to raise an alert in case the host s vehicle departs from the lane. Its functions include image-processing filters, like Gaussian smoothing and Edge detection, and blocks specifically tailored for lane marking detections.

3
Multi-Channel Video Recording ADAS Kit
The logiRECORDER Multi-Channel Video Recording Advanced Driver Assistance (ADAS) Kit builds on the Xilinx Zynq-7000 All Programmable SoC based Xylon logiADAK Automotive Driver Assistance kit by includ...

4
Objects Detector
The logiHOG is an HOG/SVM-based object detection logicBRICKS IP core for detection of multiple objects in vision-based embedded applications. It is a direct successor of the logiPDET Pedestrian Detector IP core.

5
Stepper Motors Controller
The logiSTEP is a stepper motor controller IP from Xylon IP library logicBRICKS. It enables a simultaneous control of 1 to 16 two-phase stepper motors and supports different control methods: full-step, half-step and microstepping.

6
Vehicle Detector
The logiVDET is a learning-based vehicle detection IP core, developed for vision-based embedded applications. The algorithm follows a discriminative approach based on a cascaded classifier using Local...

7
AGICIP CarM - Car Memory
CarM (Car Memory) solutions is to support the ADAS (Advanced driver-assistance systems) to help the driver in the driving process, and increase car safety and more generally road safety.

8
TES 3D Surround View - TSV
TES 3D Surround View (TSV) is the latest technology of driver assistance systems with vehicle cameras.

9
Pathpartner Drowsiness Detection
The Drowsiness Detection algorithm employs vision based driver fatigue detection methods. It is a natural, non-intrusive and convenient technique to monitor driver’s vigilance.

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