Creation of algorithms for 3D spatial-temporal data modeling

1. Silhouette : Object recognition using LiDAR

Motivation: Realizing human-like perception mechanism composed of “object separation” and “classification using silhouette shape”

Aimed function: Detection, recognition and object tracking

Application: Autonomous driving, ADAS, surveillance camera and sports analytics

Principle of Silhouette Technology

Key features :

  • Apply to any 3D sensor
  • No GPU, 6000* faster
  • Comparable to RGB in daylight
  • High performance night and day
Watch video on Youtube :

Key components of technology :

  • Separate all objects FIRST (inspired from human perception mechanism). All objects are separated and then their silhouette is extracted
  • Handle occlusions: deal with “True/Fake contour” distinctively, this system achieves good recognition even if an occlusion exists
  • By taking into account the continuity between frames, this system reduces FP/FN
  • Simple, compact silhouette descriptor of fixed size, easy to classify easy to handle, to transmit…1-2 layers NN, does not require GPU (not like CNN)
  • Training from few samples due to silhouette uniqueness
  • Accurate shape expression, even the hand in the pocket could be characterized. Silhouette technology allows easy gesture and human pose recognition

SIlhouette is a robust descriptor allowing high accuracy and real-time processing

Technology for many functions of everyday life :

(*) images are not used, LiDAR model : Velodyne – 16 planes – H=1.8m

Technology for many functions of everyday life :

(*) images are not used, LiDAR model : Velodyne – 16 planes – H=1.8m

The perfect algorithm for edge computing :

  • PROCESSING < 100ms/Lidar scan CPU: Cortex-A17, 4 cores, 1.80 GHz, RAM: 2GB, GPU: Mali-T760MP4 (no need)
  • Technology could be applied for classification of various kind of objects such as cars, cycles, poles, sitting persons…

Many applications/business based on Silhouette are possible

  • Surveillance camera, DMS (Driver Monitoring System)
  • AVG (Automated Guided Vehicle), object recognition around mobility or car
  • Understanding inside factory, sports analysis, posture recognition
  • Communication by gesture recognition

Contact us for discussing how we can meet your needs

2. Efficient combination of LiDAR intensity and 3D information for real-time pedestrian recognition

3. Needs, issues and fine estimation of vergence for self-rectification of stereo-rigs