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 Recent demos |
Real-time 3D body reconstruction
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Facial landmark tracking, expression recognition, and head pose estimation.
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Eye gaze tracking.
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Robot interact with human
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Robot facial mirroring with our facial tracking software
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Upper body body tracking and gesture recognition
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Automatic Driver Facial Behavior Tracking and Recognition
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Facial motion animation (joint work with Dr. Lijun Yin from SUNY Binghamton)
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Upperbody tracking for equation handling
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Human action and activity recognition and tracking
Activity recognition results on CAVIER dataset Activity recognition results on ISL-Activity dataset Different stages of the activity recognition process, including motion detection, object tracking and recognition
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Multiple human tracking from distance
Mulitple human tracking Human tracking and event recognition Human tracking at night with IR camera
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Real time facial feature tracking under large pose and scale changes
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Real time facial feature and 3D head pose tracking
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Worm tracking demos
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Multi-view face detection and tracking under significant head and facial expression changes
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Facial Action Units Recognition Demos
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Real Time Facial Expression Recognition Under Varying Poses
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Real Time Face and Eye Detection and Tracking
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| Older demos |
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Multiple Human Tracking with Particle Filtering Demos |
 | People and face Tracking Demo |
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Multiple-View and multipe-people face and face pose Tracking (Indoor) |
 | Human Tracking Demo(Outdoor) |
| Real Time Facial Expression Analysis demos |
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Real Time Facial Expression Analysis |
| Facial Features tracking demos |
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Real time facial features tracking 1 |
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Real time facial features tracking 2 |
| Eye gaze tracking demos |
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map control using eye gaze |
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Real time eye gaze tracking We divide the screen into 4*4 grids. We use the eye gaze to control the curosr to move among these grids. A main movement is that the cursor is moved from the top-left corner to the bottom-right corner of the screen row by row. |
| Eye tracking demos |
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Real time multi-module eye tracking 1 This demo shows robustness of eye tracker after we combine the conventional kalman filter based bright pupil tracker with the recent mean shift eye tracker. This technology can robustly track the eyes under different face orientations, external strong illuminations and closed eyes. |
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Real time multi-module eye tracking 2 |
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Real time multi-eye tracking This demo shows robustness of our eye tracker to detect and track eyes of different persons at the same time. |
| Face pose tracking demos |
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Real time face pose tracking 1 |
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Real time face pose tracking 2 |
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Real time face pose tracking 3 This demo shows robustness of our face pose tracker to detect and track face. At the same time, we do the real time face pose estimation to tell the person's face orientation. We divide the face pose into 4 types: left, right, front, up. |
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Real time face pose tracking 4 This demo shows robustness of our face pose tracker to detect and track face of different person. At the same time, we do the real time face pose estimation to tell the person's face orientation. We divide the face pose into 4 types: left, right, front, up. |
| Eyelid movement parameters tracking demos |
Eyelid movement is one of the visual behaviors refect a person's level of fatigue. There are several ocular measures to characterize eyelid movement such as eye blink frequency, eye closure duration, eye closure speed. We compute two eyelid movement parameters: PERCLOS and AECS in real time and output the two parameters to computer screen. If PERCLOS and AECS measures both exceed their respective thresholds, we issue a warning alarm.
PERCLOS measures percentage of eye closure over time, exclunding the time spent on normal closure. AECS is the average eye closure speed, which means the amount of time needed to fully close the eyes and to fully open the eyes. The eye closure speed is distinctively different for a drowsy and alert subject.
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Real time eyelid movement parameters display 1 In the screen, the upper one is the parameter of AECS and the lower one is the PERCLOS. The demo shows that when the person closes his eyes slowly, the AECS indicator will go up; When the person closes his eyes quickly, the AECS indicator will go down. If the person closes his eyes for a while, the PERCLOS indicator will go up; If the person opens his eyes for a while, the PERCLOS indicator will go down again. |
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Real time eyelid movement parameters display 2 In the screen, the upper one is the parameter of AECS and the lower one is the PERCLOS. The demo shows that when the person closes his eyes slowly, the AECS indicator will go up; When the person closes his eyes quickly, the AECS indicator will go down. If the person closes his eyes for a while, the PERCLOS indicator will go up; If the person opens his eyes for a while, the PERCLOS indicator will go down again. |
| Eye tracking demos |
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Real time pupil tracking |
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Real time pupil tracking with and without glasses
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Real time pupils tracking with wide angle camera the subject's face is within the view of the camera
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Real time eye tracking under strong external illumnation interference
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Real time eye tracking under interference of another IR light
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| Eye blink demos |
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Real time eye blink demo each time eye blinks, you hear a beep.
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| Eye switch demos |
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Real time eye switch demo the subject can turn the beep on/off by blinking three times.
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| Face Pose demos |
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Left and right face pose tracking The yellow vector represents the estimated face orientation
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Up and down face pose tracking The yellow vector represents the estimated face orientation
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| Gaze Tracking demo |
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Gaze Tracking demo1
here you will see gaze (represented by a white square) follows a red laser pointer.
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Gaze Tracking demo2
the same as example 1, except for the movement of the pointer is faster and larger.
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