Color-Based Probabilistic Tracking

By Patrick Pérez, Carine Hue, Jaco Vermaak, Michel Gangnet. European Conference on Computer Vision, 2002

1,577 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/ebc2edd037e2b3aedc72e22cda3c6d382d650058

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

Citations in the corpus

Understanding Transit Scenes: A Survey on Human Behavior-Recognition Algorithms (2010, methodology): “Therefore, tracking is performed using faces with a color particle filter [81] similar to [82].”
DeepTrack: Learning Discriminative Feature Representations by Convolutional Neural Networks for Visual Tracking (2014, methodology): “In many early methods, features are manually defined and combined [1, 5, 9, 15].”
Robust Visual Tracking via Convolutional Networks Without Training (2015, background): “These results show that all the filers, soft shrinkage, and model update components play key roles in the proposed algorithm for robust visual tracking.”
A Scale Adaptive Kernel Correlation Filter Tracker with Feature Integration (2014, methodology): “Success plots of OPE − occlusion (29) SAMF [0.613] KCF [0.514] SCM [0.487] CN [0.428] Struck [0.413] LSK [0.409] VTD [0.403] TLD [0.402] VTS [0.398] CPF [0.384] (e) 0 10 20 30 40 50 0 0.2 0.4 0.6 0.8 1 Location error threshold”
Data fusion for visual tracking with particles (2004, methodology): “The histogram-based color measurements can also be used to construct an efficient proposal for the particle filter, guiding it toward regions in the state space that are characterized by a color distribution similar to the object of interest [21], [39].”
Visual tracking decomposition (2010, methodology): “We compared the proposed algorithm (VTD) with four different tracking methods: standard MCMC (MC) based on [9][16]; Mean Shift (MS) [2] based on the implemented function in OpenCV; On-line Appearance Learning (OAL) in [17]; and Multiple Instance Learning (MIL) in [1].”
Maintaining multimodality through mixture tracking (2003, methodology): “A similar model was employed in the context of object tracking before in [ 10 ].”
Fast Online Object Tracking and Segmentation: A Unifying Approach (2018, neutral): “[13, 48, 5]).”
Staple: Complementary Learners for Real-Time Tracking (2015, methodology): “ariant to circular shifts. However, histograms alone are often insufcient to discriminate the object from the background. While colour histograms were used in many early approaches to object tracking [32,31], they have only recently been demonstrated to be competitive in modern benchmarks in the Dis”
Tracking by Sampling Trackers (2011, methodology): “Using the 7 datasets which are publicly available and 4 datasets made by us, our method (VTS) 2 was compared with five different tracking methods: standard MCMC (MC) based on [9][15], Mean Shift (MS) [4] based on the implemented function in OpenCV, Incremental Visual Tracking (IVT) in [17], Multiple”
Need for Speed: A Benchmark for Higher Frame Rate Object Tracking (2017, background): “Other types of trackers such as those in [39, 4, 28, 41] have not been considered as the state of the art over the last five years, thus, evaluating such methods on higher frame rate is outside of the scope of this work.”
Robust Object Tracking via Sparse Collaborative Appearance Model (2014, background): “, Kalman filter [1] and particle filter [2], [3]).”
An adaptive color-based particle filter (2003, methodology): “[25] introduced an approach that also uses color histograms and a particle filtering framework for multiple object tracking.”
Object Tracking with an Adaptive Color-Based Particle Filter (2002, background): “An extension for multiple objects and the usage of more than one histogram per sample can be found in [16].”
Segmentation and Tracking of Multiple Humans in Crowded Environments (2008, background): “The background exclusion concept was also proposed in [ 33 ].”