This papaer proposes a method of estimating the state of a driving lane by using a multiple-model particle filter for switching the type of multiple-lane model. This model represents whether there is a lane to the left or right of the running lane or there are lanes on both sides of the running lane. Using the context that an image is captured by car-mounted camera, we simplified the lane detec...

The paper presents the self-localization approach used by the World Champion in the Sony Four-Legged Robot League 2004. The method is based on a particle filter that makes use of different features from the environment (beacons, goals, field lines, field wall) that provide different kinds of localization information and that are recognized with different frequencies. In addition, it is discusse...

Human tracking is the process of locating moving objects (human) over time using camera. It has wide number of applications like security and surveillance, traffic control, video editing, medical imaging etc. It can be a time consuming process due to the large amount of data contained in video. The objective of human tracking is to associate target objects in consecutive video frames. To initia...

Although theorists have interpreted classical conditioning as a laboratory model of Bayesian belief updating, a recent reanalysis showed that the key features that theoretical models capture about learning are artifacts of averaging over subjects. Rather than learning smoothly to asymptote (reflecting, according to Bayesian models, the gradual tradeoff from prior to posterior as data accumulate...

Robust real-time tracking of non-rigid objects is a challenging task. Particle filtering has been proven very successful for non-linear and non-Gaussian estimation problems. However, for the tracking of non-rigid objects, the selection of reliable image features is also essential. This paper presents the integration of color distributions into particle filtering, which has typically used edge-b...

A particle filtering based block-wise estimation of true motion in a video sequence is proposed. Parameters of motion of a block in a sequence are defined as a state, and evolution of the state with respect to the block index is tracked with particle filtering. The state is assumed to be dependent on the states of neighboring blocks. Estimated motion fields are consistent and suitable for appli...

Video surveillance applications need tools to track people trajectories. We present here a new method to extract the 3D head trajectory of a person in a room using only one calibrated camera. A 3D ellipsoid representing the head is used to track the person with a hierarchical particle filter. This method can run in quasi-real-time providing reasonable 3D errors for a monocular system.

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