This paper presents an integrated approach for tracking hands, faces and specific facial features (eyes, nose, and mouth) of multiple persons in image sequences. For hand and face tracking, we employ a state-of-the-art blob tracker which is specifically trained to track skin-colored regions. The skin-color tracker is extended by incorporating an incremental probabilistic classifier used to main...

This paper presents an integrated approach for tracking hands, faces and specific facial features (eyes, nose, and mouth) in image sequences. For hand and face tracking, we employ a state-of-the-art blob tracker which is specifically trained to track skin-colored regions. The skin-color tracker is extended by incorporating an incremental probabilistic classifier, which is used to maintain and c...

Registration of endoscopic video to preoperative CT facilitates high-precision surgery of the head, neck, and skull-base. Conventional video-CT registration is limited by the accuracy of the tracker and does not use the underlying video or CT image data. A new image-based video registration method has been developed to overcome the limitations of conventional tracker-based registration. This me...

Traac statistics desired by road engineers and planners , and \traac warning" systems demand real-time performance which precludes the use of batch processing. We apply recent real-time tracking techniques along with scene speciic tuning of the dynamics to enable the tracker to accurately predict target location and thus reduce the amount of search and/or image processing required. The beneets ...

The Maximum Likelihood Probabilistic Data Association (ML-PDA) tracker and the Maximum Likelihood Probabilistic Multi-Hypothesis (ML-PMHT) tracker are applied to five synthetic benchmark multistatic active sonar scenarios featuring multiple targets, multiple sources and multiple receivers. For each of the scenarios, Monte Carlo testing is performed to quantify the performance differences betwee...

Object tracking is an important task for active vision and robotics. This paper presents a 3D feature-based tracker for tracking multiple moving objects with a computer-controlled binocular head. Our tracker operates in two phases: an initialization phase and a tracking phase. In the initial-ization phase, correspondence between 2D features in the first stereo image pair is determined reliably ...

This paper addresses the problem of attitude estimation in fractionated spacecraft clusters. Each module in the cluster may have either a startracker, a relative attitude sensor, or both. Using results in nonlinear observability theory, we provide graph-theoretic sufficient conditions for the attitude of every module to be observable. In particular we show that the attitude of every module in t...

In recent years, discriminative correlation filters (DCF) based trackers have been widely used in mobile robots due to their efficiency. However, underground coal mines are typically a low illumination environment, and tracking this environment is challenging problem that has not adequately addressed the literature. Thus, paper proposes Low-illumination Long-term Correlation Tracker (LLCT) desi...

We propose a human–robot interaction approach for social robots that attracts and controls the attention of a target person depending on her/his current visual focus of attention. The system detects the person’s current task (attention) and estimates the level by using the “task-related contextual cues” and “gaze pattern.” The attention level is used to determine the suitable time to attract th...

Accurate and robust methods for automatically tracking rolling leukocytes facilitate inflammation research as leukocyte motion is a primary indicator of inflammatory response in the microvasculature. This paper reports on an affine transformation invariance approach we proposed to track rolling leukocyte in intravital microscopy image sequences. The method is based on the affine transformation ...