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Full-Text Articles in Robotics
Combining Multiple Scoring Systems For Target Tracking Using Rank-Score Characteristics, Damian M. Lyons, D. Frank Hsu
Combining Multiple Scoring Systems For Target Tracking Using Rank-Score Characteristics, Damian M. Lyons, D. Frank Hsu
Faculty Publications
Video target tracking is the process of estimating the current state, and predicting the future state of a target from a sequence of video sensor measurements. Multitarget video tracking is complicated by the fact that targets can occlude one another, affecting video feature measurements in a highly non-linear and difficult to model fashion. In this paper, we apply a multisensory fusion approach to the problem of multitarget video tracking with occlusion. The approach is based on a data-driven method (CFA) to selecting the features and fusion operations that improve a performance criterion. Each sensory cue is treated as a scoring …
Combining Multiple Scoring Systems For Video Target Tracking Based On Rank-Score Function Variation, D. Frank Hsu, Damian M. Lyons, Jizhou Ai
Combining Multiple Scoring Systems For Video Target Tracking Based On Rank-Score Function Variation, D. Frank Hsu, Damian M. Lyons, Jizhou Ai
Faculty Publications
Tracking of video targets is the process of estimating the current and predicting the future state of a target from a sequence of video sensor measurements. Multitarget video tracking is complicated by the fact that targets can occlude one another and affect video feature measurements in a highly non-linear and difficult to model fashion., Tracking multiple targets that undergo repeated mutual occlusions is a challenging problem with several issues to be addressed. In this paper we propose a multisensory fusion approach to the problem of multitarget video tracking with occlusion. Each sensory cue is treated as a scoring system on …
Feature Selection For Real-Time Tracking, D. Frank Hsu, Damian M. Lyons, Jizhou Ai
Feature Selection For Real-Time Tracking, D. Frank Hsu, Damian M. Lyons, Jizhou Ai
Faculty Publications
We address the problem of selecting features to improve automated video tracking of targets that undergo multiple mutual occlusions. As targets are occluded, different feature subsets and combinations of those features are effective in identifying the target and improving tracking performance. We use Combinatorial Fusion Analysis to develop a metric to dynamically select which subset of features will produce the most accurate tracking. In particular we show that the combination of a pair of features A and B will improve the accuracy only if (a) A and B have relative high performance, and (b) A and B are diverse. We …