Flying pixels are one of the most common—and misunderstood—artifacts in Time-of-Flight (ToF) depth cameras. These false depth points appear near object edges and depth discontinuities, often leading to unreliable 3D perception in robotics, automation, and embedded vision systems.

In this episode of Vision Vitals by e-con Systems, we break down:

• What flying pixels are in ToF cameras
• Why they occur near edges and depth transitions
• The role of aperture size, integration time, pixel geometry, and IR interference
• How flying pixels affect AMRs, AGVs, obstacle detection, and SLAM
• Software filtering techniques like depth discontinuity and median filters
• Hardware approaches such as Mask ToF and optical control
• Best practices for reducing flying pixels in real-world deployments

Whether you’re designing robotics perception systems, industrial automation, or 3D sensing applications, this episode will help you understand how to clean up depth data and avoid false obstacles.

🔗 Explore e-con Systems Depth Cameras

Unlock the real impact of Time-of-Flight (ToF) technology with DepthVista — e-con Systems’ powerful 3D sensing camera series.

In this episode of Vision Vitals - e-con Systems Podcast, we break down the top real-world applications where DepthVista ToF cameras deliver unmatched value across robotics, healthcare, biometrics, and spatial intelligence.

You’ll discover how DepthVista enables:

🔹 Autonomous Mobile Robots (AMRs)

• Robust object detection & obstacle avoidance
• Stable depth sensing in mixed/low lighting
• Real-time mapping & localization

🔹 Pick & Place Robotics

• Precise distance measurement
• Reliable sensing on smooth or texture-less objects
• Dense depth maps for fast cycle times

🔹 AGVs (Automated Guided Vehicles)

• Consistent depth in long corridors
• Floor-level hazard detection
• Reliable navigation on predefined routes

🔹 Remote Patient Monitoring (RPM)

• Privacy-preserving depth sensing
• Non-contact fall detection & motion tracking
• Accurate performance in fully dark rooms

🔹 Biometric Security & Anti-Spoofing

• 3D facial structure validation
• Liveness detection
• Low-light authentication with active NIR illumination

We also explore upcoming opportunities for ToF cameras in:

• Spatial analytics
• Collaborative robots
• Smart retail & gesture recognition
• AR-assisted industrial workflows

DepthVista continues to push what's possible in depth sensing — and this episode shows you why.

🔗 Explore DepthVista & e-con Systems’ ToF Cameras

ToF Cameras vs. Stereo Cameras — a comparison every robotics, autonomy, and computer-vision team asks sooner or later.

In this episode of Vision Vitals by e-con Systems, we break down the real differences between these two popular depth-sensing technologies — beyond the usual textbook definitions.

Whether you're building AMRs, AGVs, cobots, warehouse automation systems, industrial inspection tools, or navigation pipelines, choosing the right 3D sensing technology can make or break your deployment.

🎧 In this episode, you’ll learn:

How They Work

• How Stereo derives depth through disparity & texture
• How ToF measures distance using NIR reflection

Where Each Technology Shines

• Low-light & featureless environments
• Texture-rich outdoor scenes
• Smooth vs dark vs reflective surfaces
• Indoor vs outdoor performance

Accuracy & Range

• Millimeter vs centimeter accuracy
• How range scales in ToF vs Stereo systems
• Why ToF excels in short-to-mid range robotics

Compute & Integration

• Processing load differences
• Stereo’s dependency on GPU resources
• Why ToF offers predictable compute paths

Cost, Reliability & Real-World Deployment

• Hardware vs software cost trade-offs
• Challenges in shadows, bright sunlight, and mixed environments
• Practical selection guidance for robotics teams
  
  

🔗 Explore e-con Systems Depth Cameras