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We describe a system for content-based retrieval from large surveillance video archives, using behavior, action and appearance of objects. Objects are detected, tracked, and classified into broad categories. Their behavior and appearance are characterized by action detectors and descriptors, which are indexed in an archive. Queries can be posed as video exemplars, and the results can be refined through...
We present a method to detect and recognize functional scene elements in video scenes. A functional scene element is a location or object that is primarily defined by its specific function or purpose, rather than its appearance or shape. Our method combines techniques from video scene analysis with functional recognition to decompose a video scene into its functional elements such as parking spots,...
Current and upcoming wide-area aerial video collectors have very large effective focal plane arrays, and can generate a tremendous amount of data. This presents significant challenges for onboard storage and for real-time downlink. This paper presents the results of an evaluation of a number of different image and video compression schemes on wide-area video. In general, we found that video compression...
Existing approaches to detect modeled activities in video often require the precise specification of the number of actors or roles, or spatial constraints, or other limitations that create difficulties for generic detection of group activities. We develop an approach to detect group behaviors in video, where an arbitrary number of participants are involved. We address scene conditions with non-participating...
We present a novel approach to learning motion behavior in video, and detecting abnormal behavior, using hierarchical clustering of hidden Markov models (HMMs). A continuous stream of track data is used for online and on-demand creation and training of HMMs, where tracks may be of highly variable length and scenes may be very complex with an unknown number of motion patterns. We show how these HMMs...
As video tracking research matures, the issue of tracker performance evaluation has emerged as a research topic in its own right, as evidenced by a series of workshops devoted solely to this purpose (the workshops on performance evaluation of tracking and surveillance-PETS). However, evaluations such as PETS have been limited to small scenarios with a handful of moving objects. In this paper, we present...
Complete and accurate video tracking is very difficult to achieve in practice due to long occlusions, traffic clutter, shadows and appearance changes. In this paper, we study the feasibility of event recognition when object tracks are fragmented. By changing the lock score threshold controlling track termination, different levels of track fragmentation are generated. The effect on event recognition...
We present a novel method for joint segmentation and pixelwise classification of images, classifying each pixel in the image into one of a set of broad categories. We propose a 2-step approach for this problem, first estimating image structure through dense region segmentation, which provides initial spatial grouping (superpixels), then performing recognition by classifying each superpixel according...
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