Car Pose Estimation


Operating from an elevated perspective, the Car Pose Estimation algorithm is effective across a wide range of environments from urban to rural. Use this model as a part of your ADAS system to predict vehicle movements, or for smart city applications, traffic analytics, insurance purposes, or intelligent transportation systems. This algorithm is made possible by CVEDIA synthetic data technology, enabling accurate interpretation of car yaw, pitch, and roll across a given camera’s field of view, and is effective in both low lighting conditions and inclement weather.



CVEDIA | Car Pose EstimationCVEDIA | Car Pose EstimationCVEDIA | Car Pose EstimationCVEDIA | Car Pose EstimationCVEDIA | Car Pose Estimation



PERFORMANCE

Optimized for edge performance with a low power profile.

RANGE

Up to 300 meters.

CONDITIONS

Dawn to dusk.

ENVIRONMENT

Environmentally-agnostic performance.

ARCHITECTURE

Backbone: Resnet-101; Detector: RefineDet.

FUNCTIONALITY

Detection.

INPUT SIZE

512x512.

SENSOR MODALITY

Visible light.



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Our services


  • MAINTENANCE

Each CVEDIA model comes backed with an ongoing maintenance agreement. Our team is available for continuous improvements and to ensure upkeep.


  • FINE GRAIN CLASSIFICATION

Speak to our team to discuss model classification as a service add on or as a separate model. CVEDIA’s in-house team will work with you to define your requirements, and build a synthetic-based model incorporating your classification specifications.


  • ADDITIONAL CLASSES

CVEDIA models are built using proprietary synthetic data technology, meaning adding additional classes to your model is possible in a matter of weeks.

Use cases


  • ADAS AND VEHICLES

Use this algorithm as a part of your ADAS or autonomous driving system to track and predict car positions. The Car Pose Estimation functions in low lighting and inclement weather, and is effective in heavy traffic and complex urban environments.


  • SMART CITIES

Use it as a reliable component of your smart intersection grid, to analyze traffic movements and behavior, and to track car movements in real-time.