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Encoding color information for visual tracking: Algorithms and benchmark
TLDR
This paper comprehensively encode 10 chromatic models into 16 carefully selected state-of-the-art visual trackers and performs detailed analysis on several issues, including the behavior of various combinations between color model and visual tracker, the degree of difficulty of each sequence for tracking, and how different challenge factors affect the tracking performance. Expand
Objective Assessment of Multiresolution Image Fusion Algorithms for Context Enhancement in Night Vision: A Comparative Study
TLDR
This paper conducts a comparative study on 12 selected image fusion metrics over six multiresolution image fusion algorithms for two different fusion schemes and input images with distortion and relates the results to an image quality measurement. Expand
Handbook of Multisensor Data Fusion : Theory and Practice, Second Edition
TLDR
The author’s research focused on the development of data fusion techniques for large-scale distributed decision-making in the rapidly changing environment. Expand
Minimum error bounded efficient ℓ1 tracker with occlusion detection
TLDR
An efficient L1 tracker with minimum error bound and occlusion detection which is called Bounded Particle Resampling (BPR)-L1 tracker and shows good performance as compared with several state-of-the-art trackers on challenging benchmark sequences. Expand
Minimum Error Bounded Efficient L1 Tracker with Occlusion Detection (PREPRINT)
TLDR
An efficient L1 tracker with minimum error bound and occlusion detection which is called Bounded Particle Resampling (BPR)-L1 tracker is proposed and shows good performance as compared with several state-of-the-art trackers on challenging benchmark sequences. Expand
Multiple source data fusion via sparse representation for robust visual tracking
TLDR
The proposed sparse representation approach can track the target more robustly than several state-of-the-art tracking algorithms and provides a flexible framework that can easily integrate information from different data sources. Expand
Clustered Object Detection in Aerial Images
TLDR
This paper proposes a Clustered Detection (ClusDet) network that unifies object clustering and detection in an end-to-end framework and achieves promising performance in comparison with state-of-the-art detectors. Expand
Kalman Filtering with Nonlinear State Constraints
An analytic method was developed by D. Simon and T. L. Chia to incorporate linear state equality constraints into the Kalman filter. When the state constraint was nonlinear, linearization wasExpand
Scalable sentiment classification for Big Data analysis using Naïve Bayes Classifier
TLDR
The result is encouraging in that the accuracy of NBC is improved and approaches 82% when the dataset size increases and it is demonstrated that NBC is able to scale up to analyze the sentiment of millions movie reviews with increasing throughput. Expand
High-Level Information Fusion Management and System Design
High-level information fusion is the ability of a fusion system to capture awareness and complex relations, reason over past and future events, utilize direct sensing exploitations and tacit reports,Expand
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