RESPONSIBLE COMPUTER VISION
Algorithms for people recognition with accuracy, context, and privacy.
We build computer vision systems that detect presence, count, track movement, or recognize people when there is a legal basis, a real need, and controls to match.
DIRECT ANSWER
What is people recognition algorithms?
A people recognition algorithm analyzes visual features to detect presence, tell individuals apart, or confirm identities; the right design depends on the goal, the environment, and privacy requirements.
Who it is forOperations, manufacturing, retail, security, events, and companies that need to interpret the flow or presence of people in images and video.
CONTEXT
Technical decisions with an operational view.
Not every problem calls for facial recognition. In many settings, detection, anonymous counting, short-lived tracking, or flow analysis deliver the result with less risk and less personal data processing.
EAGLE BS starts by defining the event that has to be identified, the camera conditions, the response time, and the tolerance for error. From there we choose the approach and build a dataset that represents the real environment.
When biometric identification is genuinely necessary, the project includes a review of legal basis, minimization, retention, security, explainability, and human review proportional to the impact of the decision.
OUTCOMES
What the initiative has to deliver.
Technical goals only matter when they improve security, speed, cost, experience or the ability to decide.
- 01Real-time counting and occupancy
- 02Presence and event detection
- 03Movement tracking
- 04Operational alerts
- 05Integration with cameras and systems
- 06Privacy controls by design
WHEN IT MAKES SENSE
Signs that it is time to act.
- You need to measure people flow
- The operation depends on video alerts
- Presence or access has to be confirmed
- Off-the-shelf models fail in the real environment
- Processing has to happen at the edge
- The project requires a data protection review
HOW WE WORK
From assessment to operations.
Short stages, visible criteria and knowledge transfer at every decision.
Defining the event
We turn the operational need into observable criteria.
Data and privacy
We plan collection, labeling, security, retention, and legal basis.
Model and validation
We train or adapt algorithms and measure errors by scenario.
Operation
We integrate, monitor drift, and handle exceptions.
DELIVERABLES
Clarity on what gets finished.
- Feasibility proof
- Video pipeline
- Tuned model or algorithm
- Inference API
- Event dashboard
- Risk and metrics documentation
FREQUENTLY ASKED QUESTIONS
Straight answers.
Is people recognition the same as facial recognition?
No. The term can cover detection, counting, tracking, re-identification, or facial confirmation. The least invasive option should come first whenever it solves the goal.
Can video be processed without sending everything to the cloud?
Yes. Depending on the hardware and the model, some or all of the inference can run at the edge, cutting latency and data exposure.
How do you handle data protection law?
The project has to define purpose, legal basis, minimization, retention, security, data subject rights, and an impact assessment where applicable. The legal decision belongs to the company and its counsel.
How is accuracy measured?
We measure false positives, false negatives, performance by image condition, and operational impact. A single average is rarely enough.
Technical sources and references
EVIDÊNCIA EM CAMPO
AI evaluated rigorously and wired into infrastructure.
Reproducibility, LLM evaluation, data, agents and operations are treated as parts of one system.
Inteligência Artificial
MLRC 2025 em Princeton: cinco princípios para avaliar LLMs com resultados reproduzíveis
Cinco aprendizados da EAGLE BS no MLRC 2025, no Princeton AI Lab, sobre benchmarks, determinismo, dados, transparência e avaliação robusta de LLMs.Ler artigo ↗
Google Cloud
Google Cloud Next 2025: IA, agentes e a nova infraestrutura digital
A participação da EAGLE BS no Google Cloud Next e Partner Summit 2025: Agentspace, Gemini 2.5, agentes, cloud, dados e aprendizados para clientes.Ler artigo ↗TALK TO A SPECIALIST
Tell us the situation. We help you see the best path.
A focused conversation to understand context, risk, priority and the first workable step.