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Machine Learning UOD - Universal Object Detection Architecture

Phi Algorithm Solutions Inc. is developing a series of Object Detectors based on a common efficient architecture, suitable for a streamlined dataflow.  
This efficient architecture requires no preprocessing on subwindows, and therefore allows for a high degree of resource sharing.
By only changing coefficients within the architecture, any type of arbitrary high performance detector can be achieved.
FD-1 Face Detector
The FD-1 is a general face detector and first in a series of object detectors based on the UOD architecture.  

This detector is robust to a number of slight image distortions including in-plane rotation, out-of-plane rotations, translational motion, Gaussian noise, compression artefacts, poor contrast or non-uniform lighting, partial occlusions and oversmoothing.   

The FD-1 detector attains a good balance of detection rates vs false alarms while remaining flexible with a high degree of programmability. 


PD-1 Pedestrian Detection and Tracking
 
The PD-1 is a pedestrian detector and tracker that leverages the existing UOD architecture.  

This technology is a combination of three main functions: foreground extraction, pedestrian detection, and object tracking.  

The PD-1 is robust to a number of slight image distortions and can be mapped to a number of implementations including CPU, DSP, RTL, and GPU. 


Pedestrian Demo with CNN

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