[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Zhou et al., 2015 - Google Patents

Abrupt motion tracking via nearest neighbor field driven stochastic sampling

Zhou et al., 2015

View PDF
Document ID
17422077172061581686
Author
Zhou T
Lu Y
Lv F
Di H
Zhao Q
Zhang J
Publication year
Publication venue
Neurocomputing

External Links

Snippet

Stochastic sampling based trackers have shown good performance for abrupt motion tracking so that they have gained popularity in recent years. However, conventional methods tend to use a two-stage sampling paradigm in which the search space needs to be uniformly …
Continue reading at arxiv.org (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6267—Classification techniques
    • G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/20—Analysis of motion
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10016—Video; Image sequence
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10024—Color image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6201—Matching; Proximity measures
    • G06K9/6202—Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20112—Image segmentation details
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46—Extraction of features or characteristics of the image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/20—Image acquisition
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass
    • G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer

Similar Documents

Publication Publication Date Title
Su et al. Abrupt motion tracking using a visual saliency embedded particle filter
Bae et al. Robust online multiobject tracking with data association and track management
Zhang et al. Visual tracking using spatio-temporally nonlocally regularized correlation filter
Held et al. Robust real-time tracking combining 3D shape, color, and motion
Zhang et al. Adaptive NormalHedge for robust visual tracking
Xiong et al. A structured learning-based graph matching method for tracking dynamic multiple objects
Kim et al. Uncertainty-aware semi-supervised few shot segmentation
Abdelali et al. Fast and robust object tracking via accept–reject color histogram-based method
Zhang et al. Structural pixel-wise target attention for robust object tracking
Zhou et al. Abrupt motion tracking via nearest neighbor field driven stochastic sampling
Mbelwa et al. Visual tracking tracker via object proposals and co-trained kernelized correlation filters
Gao et al. Face tracking based on differential harmony search
Kim et al. Interactive image segmentation using semi-transparent wearable glasses
Wang et al. Robust visual tracking by metric learning with weighted histogram representations
Bao et al. Robust visual tracking based on hierarchical appearance model
Karami et al. Online adaptive motion model-based target tracking using local search algorithm
Li et al. Spatiotemporal tree filtering for enhancing image change detection
Jiang et al. Automatic video tracking of Chinese mitten crabs based on the particle filter algorithm using a biologically constrained probe and resampling
Wang et al. Adaptive model updating for robust object tracking
Chen et al. Fast compressive tracking combined with Kalman filter
Song et al. Temporally-adjusted correlation filter-based tracking
Ramadan et al. Robust segmentation of moving objects in video based on spatiotemporal visual saliency and active contour model
Zhao et al. Robust object tracking using a sparse coadjutant observation model
Cao et al. Visual object tracking based on Motion-Adaptive Particle Filter under complex dynamics
Zhang et al. Uncertain motion tracking via target-objectness proposal and memory validation