Robotic vision summary

Content of this page:

• Overview
• The technology
• The SDK

Overview

Humans have a natural ability to recognize objects. Once we've seen an object, we can recognize that same object again, whether it is in the same or a different environment. But there are a growing number of tasks – from security to manufacturing – where it is more efficient, safe or cost-effective for the process of object recognition to be automated. In these cases, a computer with object recognition capabilities is used in conjunction with a camera or other visual input device.

The process of automating real-world object recognition requires very specific algorithms. These algorithms enable the computer to "recognize" an object that is presented to it by comparing it to a list of objects that have been stored in the computer's memory or a database. In order to be more like the human visual recognition process, this special type of algorithm must be able to recognize objects at different scales, rotations, poses and with variations in lighting. Oftentimes such technology applications require real-time processing, so the speed of the object recognition algorithm is also very important.

The technology

Sentisight object recognition technology enables the learning of objects and searching for learned objects in images from almost any camera, webcam, still picture or live video. The technology has these features:

• Accurate. The SentiSight algorithm provides simultaneous multiple 2D and 3D object detection and recognition, and is able to find out:
  • whether a particular object is presented in a scene;
  • where the object is located in the scene;
  • how many instances of the object are there in the scene.
  The algorithm is also able to evaluate the region an object occupies in a scene, providing additional information about the size, orientation and scale of the recognized object.
• Robust. SentiSight features high recognition quality and is tolerant to object scale, rotation and pose. The algorithm is able to compare and identify pictures even when the perspective has changed.
• Universal. The SentiSight algorithm is designed to be as universal as possible. It can support web cameras, surveillance cameras and can input images from the picture. It is tolerant to object scale, rotation, pose etc.
• Fast. SentiSight can process video streams in real time, so it can be used for real-time applications.
• Webcam capable. Though high quality cameras will provide better recognition quality, a simple webcam is enough for SentiSight operation.

SentiSight 2.0 algorithm demo application is available for downloading.

Read more about the technology.

The SDK

SentiSight 2.0 SDK is based on SentiSight object recognition technology and is intended for developers who want to use computer vision-based object recognition in their applications. SentiSight 2.0 SDK enables fully automatic and manual object learning as well as simultaneous multiple object detection and recognition in an easy, yet versatile, way.

SentiSight 2.0 SDK supports Microsoft Windows and Linux operating systems. You can download trial version of SentiSight 2.0 SDK to try it for creating your system. Read more…