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Moving vehicle detection and classification usingmultimodal data is a challenging task in data collection, audio-visual alignment, and feature selection, andeffective vehicle classification in uncontrolledenvironments. In this work, we first present a systematicway to align the multimodal data based the multimodaltemporal panorama generation. Then various types offeatures are extracted to represent...
Vehicle images captured by traffic and surveillance video cameras in various conditions usually exhibit several unexpected variations that worsen vehicle classification. These factors include occlusions, motion blur, and changes in perspective views. Complete and normalized views of vehicle images, if being able to reconstructed from the unsatisfactory data, will facilitate more accurate data labeling,...
In this work, we present a multimodal temporal panorama (MTP) representation that synchronizes visual, motion, and acoustic signatures of moving vehicles in the time axis. The MTP representation includes two layers: a synopsis layer and a snapshot layer. The temporal synopsis consists of 1) a panoramic view image (PVI) to represent vehicles' presence, which is constructed from 1D vertical detecting...
We reconstructed a three-dimensional tableau from a single realist painting-Scott Fraser's Three way vanitas (2006)-based on multiple stereo reconstruction applied to the direct image and the images in three plane mirrors depicted within the painting. The tableau contains a carefully chosen complex arrangement of objects including a moth, egg cup, and strand of string, glass of water, bone, and hand...
3D models of large-scale scenes available on the Internet today are largely manually created. Thus it takes a long time to create them for cities and update them as those cities that are already modeled continue to change. Multiple parallel-perspective mosaics can be generated from video automatically and more efficiently and can be used to reconstruct 3D scenes faster. A lot of video currently exists...
This paper presents a framework to analyze a large amount of video data and extract high-level structural information - planar structures and motion information - in typical urban scenes, which may be used in video coding or object recognition. The method consists of two phases. In the first phase, multiple parallel-perspective (pushbroom) mosaics are generated from the video data. In the second phase,...
In this paper, a unified, segmentation-based approach is proposed to deal with both stereo reconstruction and moving objects detection problems using multiple stereo mosaics. Each set of parallel-perspective (pushbroom) stereo mosaics is generated from a video sequence captured by a single video camera. First a color-segmentation approach is used to extract the so-called natural matching primitives...
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