Three experiments investigated the mental representation of meaningful event sequences. Experiment 1 used extended (5 min long) naturalistic scenes excerpted from commercial movies. Experiments 2 and 3 presented everyday activities by means of sequences of six photographs. All experiments found both left-right and distance effects in an order decision task, suggesting that when contemplated in ...

We present a new compression algorithm for video sequences of indoor scenes, or more generally, sequences containing mostly planar and near-planar surfaces. Our approach utilizes edge and optical flow information in order to segment selected keyframes into regions of general shape, such that the motion of each region is predicted well by a planar homography. With this kind of motion prediction,...

This paper describes an approach for automatically detecting action sequences in movies. We examine the filmmaking conventions that are inherent in action sequences and use these as a basis for our analysis. A system of lowmidand highlevel features is presented that combines pure digital video analysis at the lowand mid-levels, with high-level filmmaking knowledge. A state machine is used to co...

The number of pedestrians walking the streets or gathered in public spaces is a valuable piece of information for shop owners, city governments, event organizers and many others. However, automatic counting that takes place day and night is challenging due to changing lighting conditions and the complexity of scenes with many people occluding one another. To address these challenges, this paper...

Angus2 is developed as part of a system capable of generating natural language output based on video sequences. Currently the video sequences in Angus2 is comprised of four scenes from surveillance cameras, two filming different crosswalks with pedestrians, one filming across a gas station, and one filming an intersection. Each of these video sequences features multiple objects and actors, that...

We propose a framework for observing static scenes that can be used to detect unknown objects (i.e., left luggage or lost cargo) as well as objects that were removed or changed (i.e., theft or vandalism). The core of the method is a robust background model based on on-line AdaBoost which is able to adapt to a large variety of appearance changes (e.g., blinking lights, illumination changes). How...

This paper presents a new traffic model for MPEGencoded video sequences. The hybrid Gamma/Pareto distribution is used for all three types of frames in MPEG-encoded video sequences, and the present model takes scene changes into account. The autocorrelation structure is modeled using two second-order auto-regressive (AR) processes nested with each other. One AR process is used to generate the me...

We propose a content-based 3D mosaic (CB3M) representation for long video sequences of 3D and dynamic urban scenes captured by a camera on a mobile platform. In the first phase, a set of parallel-perspective (pushbroom) mosaics with varying viewing directions is generated to capture both the 3D and dynamic aspects of the scene under the camera coverage. In the second phase, a segmentation-based...