High tracking accuracy
Detection and association tuned to your objects, cameras and conditions.
Object Tracking
Gain continuous visibility into assets, people, vehicles and products with reliable AI object tracking software built for demanding operational environments.
- Multi-objectTracked at once
- CustomYour own classes
- Multi-camOne unified view
Live tracks · Samplelive
- Pallet · ID 24Locking on…
- Forklift · ID 03Queued
- Person · ID 11Queued
- Truck · ID 07Queued
Zone alert sent to the operations dashboard
Insights
Based on analysis of video across complex tracking environments, these are the operational impacts AI object tracking can aim for.
Less manual monitoring
Operators review exceptions and alerts instead of watching every feed.
Real-time video processing
Live streams processed fast enough to act on events as they happen.
Low-latency alerts
Zone entries and exceptions reach people and systems within moments.
Tracking performance varies with footage quality, object density, occlusion, camera conditions, hardware, latency requirements and deployment environment. Figures are never guaranteed.
Services
Our services configure, deploy, integrate and maintain each tracking solution around your cameras, infrastructure, workflows, environments and performance requirements.
Zone and Event Configuration
Define tracking zones, entry and exit rules, dwell-time thresholds, restricted areas and automated responses based on operational requirements.
Multi-Camera Tracking
Maintain consistent object identities across cameras, locations, entrances, exits, temporary obstructions and changing viewing angles.
Real-Time Processing
Process live camera feeds, RTSP streams, recorded footage and event triggers with speed matched to operational needs.
Edge Deployment
Run tracking models on local hardware for faster responses, lower bandwidth usage, stronger privacy and reliable offline operation.
Systems Integration
Connect tracking outputs with dashboards, databases, ERP systems, warehouse platforms, access controls, alerts and existing surveillance infrastructure.
Model Monitoring
Monitor accuracy, latency, identity switches, missed detections and model drift before performance issues affect operational decisions.
Capabilities
Our software identifies, monitors and analyzes objects across connected environments, helping teams improve visibility, automate responses and make better operational decisions.
Object Identification
Detect object categories and distinguish similar targets using domain-trained detection, classification and re-identification models.
Continuous Monitoring
Monitor selected objects continuously across live cameras, recorded footage, smart sensors and connected operational environments.
Object Status Tracking
Track object location, movement, condition, handling events and operational status throughout monitored workflows and environments.
Movement Analysis
Analyze routes, speed, direction, dwell time, interactions and unusual movement patterns across monitored areas.
Wide-Area Visibility
Track objects across warehouses, facilities, outdoor sites, remote locations, operational zones and distributed camera networks.
AI-Powered Decisions
Identify anomalies, recognize patterns, predict events and trigger alerts or automated actions based on defined operational rules.
The Problem
Generic tracking tools often struggle when camera conditions, object volumes, operational complexity and business requirements move beyond controlled demonstrations.
Lost identities
Tracking gaps create incomplete movement histories, unreliable reporting and missed events when objects overlap, disappear or re-enter.
Delayed processing
Growing camera volumes can increase latency, drop frames, delay alerts and weaken confidence in real-time monitoring.
Declining accuracy
Models lose effectiveness as environments, layouts, lighting, products or movement patterns change without continuous retraining.
Deployment limitations
Heavy models may perform well during testing but fail on edge hardware, local servers or limited-connectivity environments.
How It Works
Object tracking in computer vision combines detection, identity association and trajectory analysis to follow objects consistently across frames and camera feeds.
Object Detection
Locate relevant objects in each frame and assign categories, confidence scores and position coordinates.
Object Association
Connect detections across frames using appearance, movement, location, confidence and historical trajectory data.
Motion Prediction
Estimate where fast-moving, hidden or temporarily missing objects are likely to appear next.
Identity Management
Preserve consistent identities through overlap, obstruction, camera transitions, disappearance and re-entry.
Performance Evaluation
Use metrics such as HOTA and MOTA to evaluate missed and false detections, identity switches and tracking consistency over time.
Technology
Technology choices for computer vision object tracking are matched to your accuracy targets, camera conditions, latency expectations, deployment environment and integration requirements.
YOLOv8
YOLO11
Faster R-CNN
Custom CNNs
Finding Objects in Every Frame
Detection models are chosen for your object classes, camera angles, lighting and the speed your hardware can sustain.
Product names are listed as examples of tools we work with. Third-party trademarks belong to their owners.
Our Process
Aarvexa's delivery process connects technical development with operational priorities, infrastructure requirements, performance goals and long-term system reliability.
Discovery
Define target objects, camera environments, workflows, alerts, integrations and measurable success criteria.
Data audit
Assess footage quality, lighting, camera placement, object visibility, occlusion, privacy and annotation requirements.
Feasibility and validation
Evaluate infrastructure and deployment options, compare detection and tracking approaches, establish benchmarks and test challenging scenarios.
Development and integration
Train models, build tracking pipelines, connect existing systems, configure infrastructure and prepare the solution for deployment.
Monitoring and optimization
Monitor performance, detect model drift, resolve tracking issues, retrain models and scale processing capacity.
Compare
Compare purpose-built object tracking software with open-source tools across accuracy, occlusion handling, maintenance, integration and cost at scale.
Accuracy
Custom software is trained on your data and environment, while open-source tools are generally built on generic datasets.
Occlusion
Custom software provides better identity tracking through overlaps; open-source tools can produce more identity switches and tracking loss.
Maintenance
Custom deployments include managed updates, monitoring and retraining, while open-source tools require ongoing internal maintenance.
Integration and scale
Custom software connects with dashboards and business systems and is optimized for larger deployments; open-source customization and support costs can rise at scale.
Engagement
Choose a delivery approach based on your current progress, deployment scope, technical resources and long-term support requirements.
POC Sprint
Validate footage, algorithms, accuracy, latency and deployment feasibility within a focused, short engagement.
Full Deployment
Build and integrate a complete tracking system covering models, pipelines, infrastructure, interfaces, testing and rollout.
Managed Retraining
Maintain performance through monitoring, data review, annotation, retraining, optimization and controlled model updates.
Industries
Our video object tracking software supports operations where movement, identity, timing, location and behavioral patterns influence performance.
Retail
Track customer movement, queues, shelf interactions, restricted areas and product activity to improve store operations.
Sports Analytics
Track players, balls, vehicles or animals across training, competition, broadcasting and performance-analysis footage.
Agriculture and Livestock
Monitor livestock identity, movement, counting, grazing activity and health-related behavior across farms and facilities.
Manufacturing
Follow components, equipment, workers and materials to improve production visibility, quality control and process efficiency.
Security and Surveillance
Track people, vehicles and unattended objects to strengthen situational awareness, incident detection and response.
Logistics
Track vehicles, packages, pallets, containers and equipment through warehouses, yards, loading areas and distribution networks.
Live operational visibility
Object tracking impactIllustrative
Tracking accuracyTuned
Manual monitoringReduced
Camera feedsIntegrated
Object tracking case study
Real-time asset tracking across multiple facilities
A logistics operator needs continuous visibility into pallets, forklifts and high-value assets across several facilities. Aarvexa can design a multi-camera object tracking system that preserves object identities, monitors movement and delivers live operational dashboards.
Re-IDobject identities kept across cameras
Many feedscombined into one operational view
Livelocations of pallets and forklifts
- Challenge: manual asset searches limited visibility, accountability and operational response.
- Solution: dashboards delivered live locations, dwell times, movement histories, restricted-zone events and exception alerts.
- Result: dashboard-ready movement data reduced manual monitoring while improving operational visibility and response.
Illustrative scenario. Details are representative, not client-specific, and outcomes vary by footage quality, object density, occlusion, hardware, latency requirements and deployment environment.
Explore a similar buildWhy Aarvexa
Aarvexa combines computer vision expertise, software engineering, systems integration and post-launch support within one delivery team. 1,000+ projects delivered and a 98% successful go-live rate.
Custom-trained models
Models are trained around your objects, environments, cameras, business rules and operational conditions.
Detection to dashboard
One team handles detection, tracking, APIs, dashboards, alerts, deployment and workflow integration.
Edge and cloud expertise
Deploy tracking across local devices, private infrastructure, public cloud or coordinated hybrid environments.
16+ years of engineering
Proven software engineering across architecture, scalability, integration, security, testing and operational reliability.
Cross-industry knowledge
Apply computer vision approaches across retail, sports, agriculture, manufacturing, logistics, construction, security and transportation.
Post-launch support
Protect long-term performance through monitoring, retraining, optimization, incident support and controlled model updates.
Explore More
Explore more object recognition solutions
Extend visual intelligence across object recognition, image analysis, apparel analysis and image-based visual search.
Object Recognition SoftwareDetect, classify, count and validate business-specific objects across images and live video.AI Image Analysis SoftwareTurn images into structured insight with custom detection, classification and analysis.Apparel DetectionRecognize clothing categories, colors, patterns and visual attributes from images and video.AI Visual SearchLet users search with an image and instantly discover visually similar products or content.
FAQ
Straight answers on object tracking, accuracy and performance, deployment and security, integration, pricing and who we are.
Object tracking software detects objects in video, assigns each a persistent identity and follows it across frames and camera feeds, so you can see where assets, people, vehicles or products are and how they move.
Pallets, forklifts, vehicles, people, packages, equipment, livestock, players, products and other objects specific to your operation. We train custom classes around what you need to follow.
Often not. We assess your existing cameras, placement, lighting and footage quality during discovery and recommend changes only where they would meaningfully improve tracking.
Open-source tools are a strong starting point but are built on generic data. Custom software is trained on your environment, handles your occlusion and identity challenges, and includes integration, monitoring and retraining.
Many teams begin with a short proof-of-concept sprint on real footage to validate accuracy, latency and feasibility before committing to a full deployment.