Categorization

We have the following categories:

Objects: Parcel, Small Load Carrier, Pallet, Other Packaging, Product, Fork Lift, AGV, Pallet truck, Label, Multiple, Container/Trailer, Conveyor Belt, Arbitrary, Other,

CV Tasks: Object Detection, Instance Segmentation, Object Re-Identification, Object Tracking, Action Recognition, 3D Object Detection, 3D Shape Reconstruction, 3D Dimension Estimation, Image Enhancement, Edge Detection, Plane Segmentation, Keypoint Matching, Activity Recognition, Pointcloud Segmetation, 3D Positioning, Augmented Reality,

Data Type: RGB, RGBD, Pointcloud, Synthetic, Real,

Approach Type: Classical Approach, Deep Learning, Fiducial Markers, Template Matching,

Application: Label Recognition, Item Recognition, Tracking and Tracing, Volume Estimation, Verify Completeness, Verify Occupancy, Verify Guidelines/Requirements, Damage and Tampering Detection, Document Analysis, Other Assistance, Pallet Handling, Depalletization, Pick-and-Place, AGVs, Order Picking, Packaging for Shipment, Quality Control, Vehicle Traffic, Inventory Management, Sorting, Verify Right Orders, Cold Storage, Delivery, Loading and Unloading, Safety, multi-level mezzanines and vertical warehouses, Recycling, Assembly and Repair, Literature Review,

Mapping

      

Objects:
  c01: Parcel
  c02: Small Load Carrier
  c03: Pallet
  c04: Other Packaging
  c05: Product
  c06: Fork Lift
  c07: AGV
  c08: Pallet truck
  c09: Label
  c20: Multiple
  c60: Container/Trailer
  c61: Conveyor Belt
  c98: Arbitrary
  c99: Other
CV Tasks:
  t01: Object Detection
  t02: Instance Segmentation
  t03: Object Re-Identification
  t04: Object Tracking
  t05: Action Recognition
  t06: 3D Object Detection
  t07: 3D Shape Reconstruction
  t08: 3D Dimension Estimation
  t60: Image Enhancement
  t61: Edge Detection
  t62: Plane Segmentation
  t63: Keypoint Matching
  t64: Activity Recognition
  t65: Pointcloud Segmetation
  t66: 3D Positioning
  t80: Augmented Reality
Data Type:
  d01: RGB
  d02: RGBD
  d03: Pointcloud
  d50: Synthetic
  d51: Real
Approach Type:
  m01: Classical Approach
  m02: Deep Learning
  m03: Fiducial Markers
  m04: Template Matching
Application:
  a01: Label Recognition
  a02: Item Recognition
  a03: Tracking and Tracing
  a04: Volume Estimation
  a05: Verify Completeness
  a06: Verify Occupancy
  a07: Verify Guidelines/Requirements
  a08: Damage and Tampering Detection
  a09: Document Analysis
  a21: Other Assistance
  a22: Pallet Handling
  a23: Depalletization
  a24: Pick-and-Place
  a25: AGVs
  a26: Order Picking
  a27: Packaging for Shipment
  a50: Quality Control
  a51: Vehicle Traffic
  a52: Inventory Management
  a60: Sorting
  a61: Verify Right Orders
  a62: Cold Storage
  a63: Delivery
  a64: Loading and Unloading
  a65: Safety
  a66: multi-level mezzanines and vertical warehouses
  a67: Recycling
  a68: Assembly and Repair
  a99: Literature Review