KEYWORDS: Cameras, Video, Detection and tracking algorithms, RGB color model, Image segmentation, Head, Pattern recognition, Video surveillance, Automatic exposure, Image processing algorithms and systems
In this paper, we address a few important image analysis problems, which are fundamental to the design of Perceptual User Interface. We use an inexpensive stationary desktop camera to collect the video streams and use them as input to the system. We present an algorithm for segmenting moving foreground object of interest from a complex, but stationary background. This algorithm can cope with illumination changes due to shadows, Automatic Exposure Correction and long term illumination changes in the environment. The segmentation is done real time and works well for both indoor and outdoor scenes. The detected foreground is recognized as human being based on head shoulder profile.
This paper presents a novel idea of a visual communication system, which can support distance teaching using a network of computers. Here the author's main focus is to enhance the quality of distance teaching by reducing the barrier between the teacher and the student, which is formed due to the remote connection of the networked participants. The paper presents an effective way of improving teacher-student communication link of an IT (Information Technology) based distance teaching scenario, using facial expression recognition results and face global and local motion detection results of both the teacher and the student. It presents a way of regenerating the facial images for the teacher-student down-link, which can enhance the teachers facial expressions and which also can reduce the network traffic compared to usual video broadcasting scenarios. At the same time, it presents a way of representing a large volume of facial expression data of the whole student population (in the student-teacher up-link). This up-link representation helps the teacher to receive an instant feed back of his talk, as if he was delivering a face to face lecture. In conventional video tele-conferencing type of applications, this task is nearly impossible, due to huge volume of upward network traffic. The authors utilize several of their previous publication results for most of the image processing components needs to be investigated to complete such a system. In addition, some of the remaining system components are covered by several on going work.
In this paper, we present a method for segmenting the interesting foreground from the background using a novel depth cue based algorithm. The input to the algorithm are two pairs of images, the first being the stereo pair corresponding to the background image only (called the background pair), and the second corresponds to the stereo pair when the object(s) of interest is present in front of the background (called the composite pair). Since we use stereo images rather than monocular images, we can utilize the fact that the interesting foreground has a depth/disparity value which is different from the corresponding values for the background. Under situations such as poor lighting conditions, or when lighting conditions change continuously, it may be quite unreliable to extract the foreground by the process of subtracting the composite image from its background counterpart, followed by a thresholding process. Also, the camera noise is usually unknown, in general. Instead, we compute the disparity image corresponding to the background stereo pair, and validate the disparity values for the composite pair. A point belonging to the foreground will certainly have a higher disparity value. Based on the novel depth cue based measure introduced in this paper, it would fail the validation process and hence would be classified as a foreground pixel. The other notable point is that the computationally expensive stereo matching process is performed offline, and hence the segmentation process is quite fast.
Conference Committee Involvement (1)
Biometric Technology for Human Identification III
17 April 2006 | Orlando (Kissimmee), Florida, United States
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