Results 201 to 210 of about 110,606 (256)

Cooperative Tracking of Vessel Trajectory by Multi-Static Passive Stations Using an MC-RMPF. [PDF]

Sensors (Basel)
Liu B, Kong L, Wu P.
europepmc   +1 more source

Multi-target positioning and motion tracking enabled by a compound meta-eye system. [PDF]

Microsyst Nanoeng
Zhang L, Zhang L, Zhao X, Li J, Cao H, Yang J, Zhang C, Wang Z, Li Y, Shi H, Zhang Z, Li J, Guo H, Xing F, Zhang Z.   +14 more
europepmc   +1 more source

Maritime urban tracking dataset in harbor environment. [PDF]

Sci Data
Dalhaug N, Nygård TA, Hinostroza M, Flemmen HD, Martens E, Stahl A, Mester R, Brekke EF.   +7 more
europepmc   +1 more source

Robust Rear-View Human Tracking for Robotic Visual Sensing: A Spatiotemporal Prediction and Multi-Modal Fusion Approach. [PDF]

Sensors (Basel)
Jia X, Xie J, Li Y, Liang J, Zhang Z.
europepmc   +1 more source

Dynamic Occlusion-Predictive Neural Network for Robust Roadside Multi-Vehicle Tracking. [PDF]

Sensors (Basel)
Wang S, Wang Y, Wang B, Wei C, Liu H.
europepmc   +1 more source

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Improved particle filters for multi-target tracking

Journal of Computational Physics, 2012
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Vasileios Maroulas, Panos Stinis
exaly   +3 more sources

Backtracking: Retrospective multi-target tracking

Computer Vision and Image Understanding, 2012
We introduce a multi-target tracking algorithm that operates on prerecorded video as typically found in post-incident surveillance camera investigation. Apart from being robust to visual challenges such as occlusion and variation in camera view, our algorithm is also robust to temporal challenges, in particular unknown variation in frame rate.
W. P. Koppen, Marcel Worring
openaire   +3 more sources

Subgraph decomposition for multi-target tracking

2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015
Tracking multiple targets in a video, based on a finite set of detection hypotheses, is a persistent problem in computer vision. A common strategy for tracking is to first select hypotheses spatially and then to link these over time while maintaining disjoint path constraints [14, 15, 24].
Siyu Tang 0001, Bjoern Andres, Mykhaylo Andriluka, Bernt Schiele   +3 more
openaire   +2 more sources

Signature-driven multi-target tracking

2010 13th International Conference on Information Fusion, 2010
Tracking multiple maneuvering targets remains a challenge because of clutter and spurious targets. We propose a Signature-Driven multiple target Tracking (SDT) method which fuses target data in spectral, spatial and temporary spaces to form signatures of targets.
Jian-Kang Wu, Shuyan Sun, Sheng Jiang 0004, Xiaoyi Ren, Zhipei Huang   +4 more
openaire   +2 more sources

Fusion gain in multi-target tracking

2010 13th International Conference on Information Fusion, 2010
This paper introduces an information quality metric and a definition for fusion gain in multi-target tracking systems. We validate the reasonableness of these quantities and illustrate the relationship between fusion gain, scenario difficulty, and tracker effectiveness.
Stefano Coraluppi, Marco Guerriero, Craig Carthel   +2 more
openaire   +2 more sources