On the public citation graph

Carrying Object Detection Using Pose Preserving Dynamic Shape Models

0 signed · 38 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1006/cviu.1995.1004openalex-snapshot
Active Shape Models-Their Training and Application
inferredcites →https://doi.org/10.1007/3-540-47967-8_6openalex-snapshot
Shape Priors for Level Set Representations
inferredcites →https://doi.org/10.1007/b97541openalex-snapshot
Geometric Level Set Methods in Imaging, Vision, and Graphics
inferredcites →https://doi.org/10.1016/0022-247x(71)90184-3openalex-snapshot
Some results on Tchebycheffian spline functions
inferredcites →https://doi.org/10.1023/a:1008078328650openalex-snapshot
CONDENSATION—Conditional Density Propagation for Visual Tracking
inferredcites →https://doi.org/10.1109/afgr.2002.1004183openalex-snapshot
Detection of people carrying objects : a motion-based recognition approach
inferredcites →https://doi.org/10.1109/cvpr.2003.1211457openalex-snapshot
Multilinear subspace analysis of image ensembles
inferredcites →https://doi.org/10.1109/cvpr.2003.1211474openalex-snapshot
Learning object intrinsic structure for robust visual tracking
inferredcites →https://doi.org/10.1109/cvpr.2004.1315070openalex-snapshot
Separating style and content on a nonlinear manifold
inferredcites →https://doi.org/10.1109/cvpr.2004.1315230openalex-snapshot
Inferring 3D body pose from silhouettes using activity manifold learning
inferredcites →https://doi.org/10.1109/iccv.1999.791204openalex-snapshot
Backpack: detection of people carrying objects using silhouettes
inferredcites →https://doi.org/10.1109/iccv.2001.937599openalex-snapshot
Probabilistic tracking in a metric space
inferredcites →https://doi.org/10.1109/jproc.2002.801448openalex-snapshot
Background and foreground modeling using nonparametric kernel density estimation for visual surveillance
inferredcites →https://doi.org/10.1109/tmi.2002.808355openalex-snapshot
A shape-based approach to the segmentation of medical imagery using level sets
inferredcites →https://doi.org/10.1109/tpami.2005.39openalex-snapshot
The humanID gait challenge problem: data sets, performance, and analysis
inferredcites →https://doi.org/10.1126/science.290.5500.2323openalex-snapshot
Nonlinear Dimensionality Reduction by Locally Linear Embedding
inferredcites →https://doi.org/10.1198/jasa.2003.s269openalex-snapshot
Learning With Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
inferredcites →https://doi.org/10.7551/mitpress/4175.001.0001openalex-snapshot
Learning with Kernels

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/s11042-018-6045-yopenalex-snapshot
Human gait recognition using localized Grassmann mean representatives with partial least squares regression
inferred← citeshttps://doi.org/10.1016/j.cviu.2006.08.002openalex-snapshot
A survey of advances in vision-based human motion capture and analysis
inferred← citeshttps://doi.org/10.1016/j.cviu.2008.10.003openalex-snapshot
Dynamic shape outlier detection for human locomotion
inferred← citeshttps://doi.org/10.1016/j.imavis.2015.11.009openalex-snapshot
A framework for semantic people description in multi-camera surveillance systems
inferred← citeshttps://doi.org/10.1016/j.patcog.2018.12.009openalex-snapshot
From superpixel to human shape modelling for carried object detection
inferred← citeshttps://doi.org/10.1109/cvprw.2013.114openalex-snapshot
Learning to Detect Carried Objects with Minimal Supervision
inferred← citeshttps://doi.org/10.1109/dicta.2008.14openalex-snapshot
Multi-view Human Motion Capture with an Improved Deformation Skin Model
inferred← citeshttps://doi.org/10.1109/icetcct.2017.8280332openalex-snapshot
Abandoned object identification and detection system for railways in India
inferred← citeshttps://doi.org/10.1109/icnc.2015.7378059openalex-snapshot
A method of carried object detection based on key posture of silhouette
inferred← citeshttps://doi.org/10.1109/icosp.2014.7015212openalex-snapshot
Carried object detection in short video sequences
inferred← citeshttps://doi.org/10.1109/jsen.2023.3295574openalex-snapshot
Carry Object Detection Utilizing mmWave Radar Sensors and Ensemble-Based Extra Tree Classifiers on the Edge Computing Systems
inferred← citeshttps://doi.org/10.1109/tifs.2013.2279797openalex-snapshot
Carried Object Detection in Videos Using Color Information
inferred← citeshttps://doi.org/10.1109/tits.2025.3569425openalex-snapshot
Passenger-Luggage Combined Motion Model and Abnormal State Recognition in Public Transportation Hubs
inferred← citeshttps://doi.org/10.1109/tpami.2011.205openalex-snapshot
Detecting Carried Objects from Sequences of Walking Pedestrians
inferred← citeshttps://doi.org/10.1109/tsmcb.2010.2044173openalex-snapshot
Applications of a Simple Characterization of Human Gait in Surveillance
inferred← citeshttps://doi.org/10.1109/wacv.2011.5711518openalex-snapshot
Detecting people carrying objects based on an optical flow motion model
inferred← citeshttps://doi.org/10.25911/5d7a2682becf6openalex-snapshot
Inferring Human Pose and Motion from Images
inferred← citeshttps://doi.org/10.2991/lemcs-15.2015.318openalex-snapshot
Detection of Object Carried Using Spatio-temporal Pattern and Local Directional Pattern Descriptor
inferred← citeshttps://doi.org/10.3390/bdcc6040108openalex-snapshot
Detection and Classification of Human-Carrying Baggage Using DenseNet-161 and Fit One Cycle
inferred← citeshttps://doi.org/10.70675/32b3404ez6643z4747zbbc5zf2a38e86e7bbopenalex-snapshot
Analyse robuste de formes basée géodésiques et variétés de formes
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.