Outsight’s software solutions track the motion of people and vehicles using 3D LiDAR data.
Operators of transportation hubs like airports and train stations but also sport venues, road infrastructures and industrial sites can now access accurate and anonymous Spatial Intelligence data, in order to improve operations and increase user safety and satisfaction.
Our international team of scientists and engineers drive the development of our solutions from Paris, San Francisco, Sophia-Antipolis (Nice) & Hong Kong. To support our global outreach, we also operate a commercial office in Spain.
You can find below an interesting link about who we are and what we do :
Our Passenger Flow Traffic Monitoring solution is trusted by the world’s leading airports and train stations across four continents, including the most renowned hubs celebrated for their operational excellence and exceptional passenger experience. We also deploy our solutions in other markets such as Tourism, Retail and Sports.
Additionally, our Car Traffic Remote Monitoring product is trusted by several Tier 1 customers, including BMW.
Position Overview
Since its creation, Outsight has been strongly oriented toward real-time processing, without truly exploring the potential of offline tracking.
The objective of this internship is to investigate backward tracking approaches as a way to enhance the robustness and accuracy of the current solution.
Backward/forward tracking leverages both past-to-future and future-to-past information to better track entities in challenging environments, where trajectories often overlap, occlude, or become ambiguous. In dense scenarios (e.g., crowds, queues) or in poorly covered areas, forward-only tracking tends to fail, whereas backward passes can refine trajectories and correct errors.
Responsibilities
Implement a data replay mechanism in the backward direction
Characterize system performance
Develop a method for associating forward and backward tracking results
Currently pursuing a degree in Computer Science, Robotics, Electrical Engineering, or a related field
Familiarity with tracking algorithms (e.g., Kalman filter, particle filter, or deep learning-based approaches)
Proficiency in Python
Strong analytical and problem-solving skills
Why join us?
Be part of the team pioneering Spatial Intelligence solutions at unprecedented scale—the breakthrough technology transforming how the world’s most prestigious airports, infrastructure operators, and smart cities understand and optimize physical flows.
As a 7-time Gartner-recognized category-defining leader with dozens of global awards including “Edge AI Product of the Year,” “LiDAR Leader Award,” “CES Best of Innovation” and many more, we’re backed by 37 patents and deployments with the most prestigious (and challenging) customers across four continents.
Join our international team of world-class experienced engineers and business leaders solving humanity’s most complex spatial challenges, from passenger flow optimization to autonomous robotics coordination, while working at the cutting edge of 3D AI, LiDAR perception, and real-time analytics.
Supported by rock-solid investors including BNP Paribas, BPI France, Energy Innovation Capital and Demeter who back our long-term vision, this is your opportunity to shape how physical and digital worlds interact, with the resources, growth trajectory, and technical challenges that will accelerate your career in ways traditional companies cannot offer.
Outsight is an Equal Employment Opportunity employer that pursues and hires a diverse workforce. Outsighters don't make employment decisions on the basis of race, color, religion, ethnic or national origin, nationality, sex, gender, gender identity, sexual orientation, disability, age, military status, or any other basis protected by local, state, or federal laws. Outsight also strives for a healthy and safe workplace, and prohibits harassment of any kind. If you have a disability or special need that requires accommodation, please let us know.
Add a comment
Outsight’s software solutions track the motion of people and vehicles using 3D LiDAR data.
Operators of transportation hubs like airports and train stations but also sport venues, road infrastructures and industrial sites can now access accurate and anonymous Spatial Intelligence data, in order to improve operations and increase user safety and satisfaction.
Our international team of scientists and engineers drive the development of our solutions from Paris, San Francisco, Sophia-Antipolis (Nice) & Hong Kong. To support our global outreach, we also operate a commercial office in Spain.
You can find below an interesting link about who we are and what we do :
Our Passenger Flow Traffic Monitoring solution is trusted by the world’s leading airports and train stations across four continents, including the most renowned hubs celebrated for their operational excellence and exceptional passenger experience. We also deploy our solutions in other markets such as Tourism, Retail and Sports.
Additionally, our Car Traffic Remote Monitoring product is trusted by several Tier 1 customers, including BMW.
Position Overview
Since its creation, Outsight has been strongly oriented toward real-time processing, without truly exploring the potential of offline tracking.
The objective of this internship is to investigate backward tracking approaches as a way to enhance the robustness and accuracy of the current solution.
Backward/forward tracking leverages both past-to-future and future-to-past information to better track entities in challenging environments, where trajectories often overlap, occlude, or become ambiguous. In dense scenarios (e.g., crowds, queues) or in poorly covered areas, forward-only tracking tends to fail, whereas backward passes can refine trajectories and correct errors.
Responsibilities
Implement a data replay mechanism in the backward direction
Characterize system performance
Develop a method for associating forward and backward tracking results
Currently pursuing a degree in Computer Science, Robotics, Electrical Engineering, or a related field
Familiarity with tracking algorithms (e.g., Kalman filter, particle filter, or deep learning-based approaches)
Proficiency in Python
Strong analytical and problem-solving skills
Why join us?
Be part of the team pioneering Spatial Intelligence solutions at unprecedented scale—the breakthrough technology transforming how the world’s most prestigious airports, infrastructure operators, and smart cities understand and optimize physical flows.
As a 7-time Gartner-recognized category-defining leader with dozens of global awards including “Edge AI Product of the Year,” “LiDAR Leader Award,” “CES Best of Innovation” and many more, we’re backed by 37 patents and deployments with the most prestigious (and challenging) customers across four continents.
Join our international team of world-class experienced engineers and business leaders solving humanity’s most complex spatial challenges, from passenger flow optimization to autonomous robotics coordination, while working at the cutting edge of 3D AI, LiDAR perception, and real-time analytics.
Supported by rock-solid investors including BNP Paribas, BPI France, Energy Innovation Capital and Demeter who back our long-term vision, this is your opportunity to shape how physical and digital worlds interact, with the resources, growth trajectory, and technical challenges that will accelerate your career in ways traditional companies cannot offer.
Outsight is an Equal Employment Opportunity employer that pursues and hires a diverse workforce. Outsighters don't make employment decisions on the basis of race, color, religion, ethnic or national origin, nationality, sex, gender, gender identity, sexual orientation, disability, age, military status, or any other basis protected by local, state, or federal laws. Outsight also strives for a healthy and safe workplace, and prohibits harassment of any kind. If you have a disability or special need that requires accommodation, please let us know.
Add a comment
Outsight’s software solutions track the motion of people and vehicles using 3D LiDAR data.Operators of transportation hubs like airports and train stations but also sport venues, road infrastructures and industrial sites can now access accurate and anonymous Spatial Intelligence data, in order to improve operations and increase user safety and satisfaction.Our international team of scientists and engineers drive the development of our solutions from Paris, San Francisco, Sophia-Antipolis (Nice) & Hong Kong. To support our global outreach, we also operate a commercial office in Spain.You can find below an interesting link about who we are and what we do :Insights about OutsightOur Passenger Flow Traffic Monitoring solution is trusted by the world’s leading airports and train stations across four continents, including the most renowned hubs celebrated for their operational excellence and exceptional passenger experience. We also deploy our solutions in other markets such as Tourism, Retail and Sports.Additionally, our Car Traffic Remote Monitoring product is trusted by several Tier 1 customers, including BMW.Position OverviewSince its creation, Outsight has been strongly oriented toward real-time processing, without truly exploring the potential of offline tracking.The objective of this internship is to investigate backward tracking approaches as a way to enhance the robustness and accuracy of the current solution.Backward/forward tracking leverages both past-to-future and future-to-past information to better track entities in challenging environments, where trajectories often overlap, occlude, or become ambiguous. In dense scenarios (e.g., crowds, queues) or in poorly covered areas, forward-only tracking tends to fail, whereas backward passes can refine trajectories and correct errors.Responsibilities Implement a data replay mechanism in the backward directionCharacterize system performanceDevelop a method for associating forward and backward tracking resultsClassify object trajectories (valid, invalid, uncertain)Automatically detect error casesPropose and implement improvementsRequirements for the roleCurrently pursuing a degree in Computer Science, Robotics, Electrical Engineering, or a related fieldFamiliarity with tracking algorithms (e.g., Kalman filter, particle filter, or deep learning-based approaches)Proficiency in PythonStrong analytical and problem-solving skillsWhy join us? Be part of the team pioneering Spatial Intelligence solutions at unprecedented scale—the breakthrough technology transforming how the world’s most prestigious airports, infrastructure operators, and smart cities understand and optimize physical flows.As a 7-time Gartner-recognized category-defining leader with dozens of global awards including “Edge AI Product of the Year,” “LiDAR Leader Award,” “CES Best of Innovation” and many more, we’re backed by 37 patents and deployments with the most prestigious (and challenging) customers across four continents.Join our international team of world-class experienced engineers and business leaders solving humanity’s most complex spatial challenges, from passenger flow optimization to autonomous robotics coordination, while working at the cutting edge of 3D AI, LiDAR perception, and real-time analytics.Supported by rock-solid investors including BNP Paribas, BPI France, Energy Innovation Capital and Demeter who back our long-term vision, this is your opportunity to shape how physical and digital worlds interact, with the resources, growth trajectory, and technical challenges that will accelerate your career in ways traditional companies cannot offer.Outsight is an Equal Employment Opportunity employer that pursues and hires a diverse workforce. Outsighters don't make employment decisions on the basis of race, color, religion, ethnic or national origin, nationality, sex, gender, gender identity, sexual orientation, disability, age, military status, or any other basis protected by local, state, or federal laws. Outsight also strives for a healthy and safe workplace, and prohibits harassment of any kind. If you have a disability or special need that requires accommodation, please let us know. Add a comment
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