Face on Edge: Real Time Face Recognition on Snapdragon 845
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Face on Edge: Real Time Face Recognition on Snapdragon 845
Description
Face recognition is an algorithm/technique to identify faces by their names/IDs. A face recognition system captures an incoming image from a camera, crops and localizes the face, and extracts unique features from it. These features help build a classification model to recognize/classify faces. This paper’s purpose is to develop a face recognition system and deploy it on the Eragon 845 board, a Hardware Development Kit (HDK) featuring the Qualcomm® Snapdragon™ SD845 processor. The developed face recognition application is tested on Oneplus 6, an Android-based mobile device built
on a Snapdragon™ SD845 processor. The classification model, Extreme Value Machine (EVM) , was recreated in Java Android, and the produced application’s performance was evaluated on the device’s
various runtimes (CPU, GPU, GPU_Float16, and DSP).
In this whitepaper we have discussed how we have developed and deployed the Real Time Face Recognition on the Eragon 845 and tested on the Oneplus 6 phone, both of which are based on the SD 845 SoC.
Highlights
- Snapdragon Neural Processing Engine (SNPE)
- Facial recognition pipeline
- SSD MobileNet FaceNet
- Extreme value machine Performance of face recognition pipeline
- Facial recognition application demonstration
- Application Area
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Description
Face recognition is an algorithm/technique to identify faces by their names/IDs. A face recognition system captures an incoming image from a camera, crops and localizes the face, and extracts unique features from it. These features help build a classification model to recognize/classify faces. This paper’s purpose is to develop a face recognition system and deploy it on the Eragon 845 board, a Hardware Development Kit (HDK) featuring the Qualcomm® Snapdragon™ SD845 processor. The developed face recognition application is tested on Oneplus 6, an Android-based mobile device built
on a Snapdragon™ SD845 processor. The classification model, Extreme Value Machine (EVM) , was recreated in Java Android, and the produced application’s performance was evaluated on the device’s
various runtimes (CPU, GPU, GPU_Float16, and DSP).
In this whitepaper we have discussed how we have developed and deployed the Real Time Face Recognition on the Eragon 845 and tested on the Oneplus 6 phone, both of which are based on the SD 845 SoC.
Highlights
- Snapdragon Neural Processing Engine (SNPE)
- Facial recognition pipeline
- SSD MobileNet FaceNet
- Extreme value machine Performance of face recognition pipeline
- Facial recognition application demonstration
- Application Area
To download this resource
Fill in the details below
Description
Face recognition is an algorithm/technique to identify faces by their names/IDs. A face recognition system captures an incoming image from a camera, crops and localizes the face, and extracts unique features from it. These features help build a classification model to recognize/classify faces. This paper’s purpose is to develop a face recognition system and deploy it on the Eragon 845 board, a Hardware Development Kit (HDK) featuring the Qualcomm® Snapdragon™ SD845 processor. The developed face recognition application is tested on Oneplus 6, an Android-based mobile device built
on a Snapdragon™ SD845 processor. The classification model, Extreme Value Machine (EVM) , was recreated in Java Android, and the produced application’s performance was evaluated on the device’s
various runtimes (CPU, GPU, GPU_Float16, and DSP).
In this whitepaper we have discussed how we have developed and deployed the Real Time Face Recognition on the Eragon 845 and tested on the Oneplus 6 phone, both of which are based on the SD 845 SoC.
Highlights
- Snapdragon Neural Processing Engine (SNPE)
- Facial recognition pipeline
- SSD MobileNet FaceNet
- Extreme value machine Performance of face recognition pipeline
- Facial recognition application demonstration
- Application Area
To download this resource
Fill in the details below
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