JeVois Intro
Simple introduction to JeVois and demo that combines saliency, gist, face detection, and object recognition.
By Laurent Ittiitti@usc.eduhttp://jevois.orgGPL v3
Video Mapping:   YUYV 640 360 50.0 YUYV 320 240 50.0 JeVois JeVoisIntro
Video Mapping:   YUYV 640 480 50.0 YUYV 320 240 50.0 JeVois JeVoisIntro

Module Documentation

This module plays an introduction movie, and then launches the equivalent of DemoSalGistFaceObj, but with some added text messages that explain what is going on on the screen.

ParameterTypeDescriptionDefaultValid Values
(Saliency) cweightbyteColor channel weight255-
(Saliency) iweightbyteIntensity channel weight255-
(Saliency) oweightbyteOrientation channel weight255-
(Saliency) fweightbyteFlicker channel weight255-
(Saliency) mweightbyteMotion channel weight255-
(Saliency) centerminsize_tLowest (finest) of the 3 center scales2-
(Saliency) deltaminsize_tLowest (finest) of the 2 center-surround delta scales3-
(Saliency) smscalesize_tScale of the saliency map4-
(Saliency) mthreshbyteMotion threshold0-
(Saliency) fthreshbyteFlicker threshold0-
(Saliency) msflickboolUse multiscale flicker computationfalse-
(FaceDetector) face_cascadestd::stringFile name of the face cascadefacedetector/haarcascade_frontalface_alt.xml-
(FaceDetector) eye_cascadestd::stringFile name of the eye cascade, or empty to not detect eyesfacedetector/haarcascade_eye_tree_eyeglasses.xml-
(Kalman2D) usevelboolUse velocity tracking, in addition to positionfalse-
(Kalman2D) procnoisefloatProcess noise standard deviation0.003F-
(Kalman2D) measnoisefloatMeasurement noise standard deviation0.05F-
(Kalman2D) postnoisefloatA posteriori error estimate standard deviation0.3F-
(BufferedVideoReader) filenamestd::stringFilename of video to read (if not absolute, will be assumed to be relative to Component path)movie.mpg-
Detailed docs:JeVoisIntro, Saliency, FaceDetector, ObjectRecognitionMNIST, Kalman2D, BufferedVideoReader
Copyright:Copyright (C) 2016 by Laurent Itti, iLab and the University of Southern California
License:GPL v3
Support URL:
Other URL:
Address:University of Southern California, HNB-07A, 3641 Watt Way, Los Angeles, CA 90089-2520, USA