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Counting pedestrians in video sequences using trajectory clustering

Related publications (36)

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Finding Audio-Visual Events in Informal Social Gatherings

In this paper we address the problem of detecting and localizing objects that can be both seen and heard, e.g., people. This may be solved within the framework of data clustering. We propose a new multimodal clustering algorithm based on a Gaussian mixture ...

2011

A Clustering Method Based on Soft Learning of Model (Prototype) and Dissimilarity Metrics

Arash Arami

Many clustering methods are designed for especial cluster types or have good performance dealing with particular size and shape of clusters. The main problem in this connection is how to define a similarity (or dissimilarity) criterion to make an algorithm ...

Springer-Verlag2009

Appearance-based Keypoint Clustering

Pascal Fua, Sabine Süsstrunk, Vincent Lepetit, Francisco Estrada

We present an algorithm for clustering sets of detected interest points into groups that correspond to visually distinct structure. Through the use of a suitable colour and texture representation, our clustering method is able to identify keypoints that be ...

2009

Fast high-dimensional Bayesian classification and clustering

Vahid Partovi Nia

We introduce a fast approach to classification and clustering applicable to high-dimensional continuous data, based on Bayesian mixture models for which explicit computations are available. This permits us to treat classification and clustering in a single ...

EPFL2009

Learning Cluster Type and Dissimilarity Metric for Each Cluster Using a Set of Possible Cluster Types

Arash Arami

One of the shortcomings of the existing clustering methods is their problems dealing with different shape and size clusters. On the other hand, most of these methods are designed for especial cluster types or have good performance dealing with particular s ...

2007

A discrete choice modeling framework for pedestrian walking behavior with application to human tracking in video sequences

Gianluca Antonini

Intelligent Transportation Systems (ITS) have triggered important research activities in the context of behavioral dynamics. Several new models and simulators for driving and travel behaviors, along with new integrated systems to manage various elements of ...

EPFL2005

Kernelized Infomax Clustering

We propose a simple information-theoretic clustering approach based on maximizing the mutual information

I(\sfx,y)

between the unknown cluster labels

y

and the training patterns

\sfx

with respect to parameters of specifically constrained encoding dis ...

IDIAP2005

Multi-layer hierarchical clustering of pedestrian trajectories for automatic counting of people in video sequences

Jean-Philippe Thiran, Gianluca Antonini

In this paper we propose an approach to count the number of pedestrians, given a trajectory data set provided by a tracking system. The tracking process itself is treated as a black box providing us the input data. The idea is to apply a hierarchical clust ...

IEEE2005

Making Retrieval Faster Through Document Clustering

David Grangier, Alessandro Vinciarelli

This work addresses the problem of reducing the time between query submission and results output in a retrieval system. The goal is achieved by considering only a database fraction as small as possible during the retrieval process. Our approach is based on ...

IDIAP2004

Noisy Text Clustering