objectspots

Objectspots are markers or fiducials placed on physical objects to help computer vision systems recognize, locate, and track those objects in a scene. They provide identifiable reference features that can be detected by cameras and processed by software to estimate an object's pose, including its position and orientation, and sometimes its scale. The term objectspot is used in various contexts to describe either standardized markers or practical marker patterns applied to objects.

Designs for objectspots typically rely on high-contrast patterns that can be recognized from multiple angles. Common implementations mimic fiducial marker families such as square binary patterns or dot-based codes, though organizations may develop custom patterns tailored to a specific workflow. A detector identifies the pattern, decodes its identity, and then computes the object's pose relative to the camera using pre-established camera calibration parameters.

Performance considerations include robustness to occlusion, lighting variation, and perspective distortion. Objectspots are often printed on durable labels or directly on object surfaces, and may be embedded into 3D models for simulation. They can be applied to a single object or distributed on multiple faces to improve pose estimation accuracy.

Applications span robotics (grasping, navigation), industrial automation (object tracking on assembly lines), augmented reality (overlaying graphics on real objects), and quality control (verifying object orientation).

Origin and usage: The term is not tied to a single standard, and its precise meaning can vary by domain. In academic and industrial practice, objectspots are part of marker-based localization systems that complement or replace natural feature tracking when precise pose information is required.