Computer vision is opening up possibilities of adding differentiating capabilities in high-tech products by enabling these products to see and understand the world around them better. However, computer vision is computationally intensive – it consumes prohibitive amount of resources including CPU and memory. Add to that the challenge of achieving accuracy requirements and it becomes a huge adoption barrier. PathPartner, with its extensive expertise in image/video processing algorithms, deep learning methodologies and embedded systems, enables customers to harness the power of computer vision technologies in their next-gen products.

Full stack service offerings

Proof-of-concept development
  • Algorithm prototype development using openCV, MatLab, Octave, Eigen Library, Point Cloud Library (PCL)
Algorithm development & tuning
  • Data set collection and annotation of video data
  • Tuning of algorithms
Platform optimization
  • Porting and optimizations on embedded platforms
  • Deep compression for embedded platforms
  • GPU acceleration and model conversion tools

Our experience spans a wide range of algorithmsthat can be tuned for various industries

Face detection and recognition
Motion detection and tracking
Audience measurement
3D depth map
Gesture recognition

Our expertise in action: PathPartner’s Driver Monitoring solution

PathPartner’s driver monitoring solution, uses advanced deep learning methodologies to assess drivers’ alertness under diverse conditions. It uses a hybrid combination of advanced facial analysis algorithms across 28 facial landmarks to perform real time analysis of driver’s eyes, mouth, and head movements. With a thorough study on each of these problems complexity, deep understanding of deep learning models’ representation abilities, we developed algorithms that can run real time on embedded systems (Ex: our DMS can run real time on Qualcomm's SD820 and NVidia TX2)

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