The proceedings contain 99 papers. The topics discussed include: fast fragment assemblage using boundary line and surface matching;archaeological fragment reconstruction using curve-matching;profile-based pottery reco...
ISBN:
(纸本)0769519008
The proceedings contain 99 papers. The topics discussed include: fast fragment assemblage using boundary line and surface matching;archaeological fragment reconstruction using curve-matching;profile-based pottery reconstruction;accurately estimating sherd 3D surface geometry with application to pot reconstruction;application of structured illumination in nano-scale vision;noise adaptive channel smoothing of low-dose images;indirect symbolic correlation approach to unsegmented text recognition;background line detection with a stochastic model;estimating tracking sources and sinks;generic event detection in sports video using cinematic features;towards perceptual interface for visualization navigation of large data sets;coevolutionary computation for synthesis of recognition systems;mirror shape recovery from image curves and intrinsic parameters: rotationally symmetric and conic mirrors;parametric subpixel matchpoint recovery with uncertainty estimation: a statistical approach;and tracking random sets of vehicles in terrain.
The proceedings contain 99 papers. The topics discussed include: fast fragment assemblage using boundary line and surface matching;archaeological fragment reconstruction using curve-matching;profile-based pottery reco...
ISBN:
(纸本)0769519008
The proceedings contain 99 papers. The topics discussed include: fast fragment assemblage using boundary line and surface matching;archaeological fragment reconstruction using curve-matching;profile-based pottery reconstruction;accurately estimating sherd 3D surface geometry with application to pot reconstruction;application of structured illumination in nano-scale vision;noise adaptive channel smoothing of low-dose images;indirect symbolic correlation approach to unsegmented text recognition;background line detection with a stochastic model;estimating tracking sources and sinks;generic event detection in sports video using cinematic features;towards perceptual interface for visualization navigation of large data sets;coevolutionary computation for synthesis of recognition systems;mirror shape recovery from image curves and intrinsic parameters: rotationally symmetric and conic mirrors;parametric subpixel matchpoint recovery with uncertainty estimation: a statistical approach;and tracking random sets of vehicles in terrain.
The proceedings contain 99 papers. The topics discussed include: fast fragment assemblage using boundary line and surface matching;archaeological fragment reconstruction using curve-matching;profile-based pottery reco...
ISBN:
(纸本)0769519008
The proceedings contain 99 papers. The topics discussed include: fast fragment assemblage using boundary line and surface matching;archaeological fragment reconstruction using curve-matching;profile-based pottery reconstruction;accurately estimating sherd 3D surface geometry with application to pot reconstruction;application of structured illumination in nano-scale vision;noise adaptive channel smoothing of low-dose images;indirect symbolic correlation approach to unsegmented text recognition;background line detection with a stochastic model;estimating tracking sources and sinks;generic event detection in sports video using cinematic features;towards perceptual interface for visualization navigation of large data sets;coevolutionary computation for synthesis of recognition systems;mirror shape recovery from image curves and intrinsic parameters: rotationally symmetric and conic mirrors;parametric subpixel matchpoint recovery with uncertainty estimation: a statistical approach;and tracking random sets of vehicles in terrain.
Detecting suspicious events from video surveillance cameras has been an important task recently. Many trajectory based descriptors were developed, such as to detect people running or moving in opposite direction. Howe...
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Detecting suspicious events from video surveillance cameras has been an important task recently. Many trajectory based descriptors were developed, such as to detect people running or moving in opposite direction. However, these trajectory based descriptors are not working well in the crowd environments like airports, rail stations, because those descriptors assume perfect motion/object segmentation. In this paper, we present an event detection method using dynamic texture descriptor. The dynamic texture descriptor is an extension of the local binary patterns. The image sequences are divided into regions. A flow is formed based on the similarity of the dynamic texture descriptors on the regions. We used real dataset for experiments. The results are promising.
One of the main challenges in computervision is the automatic detection of specific object classes in images. Recent advances of object detection performance in the visible spectrum encourage the application of these...
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ISBN:
(纸本)9781424439942
One of the main challenges in computervision is the automatic detection of specific object classes in images. Recent advances of object detection performance in the visible spectrum encourage the application of these approaches to data beyond the visible spectrum. In this paper, we show the applicability of a well known, local-feature based object detector for the case of people detection in thermal data. We adapt the detector to the special conditions of infrared data and show the specifics relevant for feature based object detection. For that, we employ the SURF feature detector and descriptor that is well suited for infrared data. We evaluate the performance of our adapted object detector in the task of person detection in different real-world scenarios where people occur at multiple scales. Finally, we show how this local-feature based detector can be used to recognize specific object parts, i.e., body parts of detected people.
Matching vehicles subject to both large pose transformations and extreme illumination variations remains a technically challenging problem in computervision. In this paper, we develop a new and robust framework towar...
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ISBN:
(纸本)9781424439942
Matching vehicles subject to both large pose transformations and extreme illumination variations remains a technically challenging problem in computervision. In this paper, we develop a new and robust framework toward matching and recognizing vehicles with both highly varying poses and drastically changing illumination conditions. By effectively estimating both pose and illumination conditions, we can re-render vehicles in the reference image to generate the relit image with the same pose and illumination conditions as the target image. We compare the relit image and the re-rendered target image to match vehicles in the original reference image and target image. Furthermore, no training is needed in our framework and re-rendered vehicle images in any other viewpoints and illumination conditions can be obtained from just one single input image. Experimental results demonstrate the robustness and efficacy of our framework, with a potential to generalize our current method from vehicles to handle other types of objects.
The proceedings contain 99 papers. The topics discussed include: fast fragment assemblage using boundary line and surface matching;archaeological fragment reconstruction using curve-matching;profile-based pottery reco...
ISBN:
(纸本)0769519008
The proceedings contain 99 papers. The topics discussed include: fast fragment assemblage using boundary line and surface matching;archaeological fragment reconstruction using curve-matching;profile-based pottery reconstruction;accurately estimating sherd 3D surface geometry with application to pot reconstruction;application of structured illumination in nano-scale vision;noise adaptive channel smoothing of low-dose images;indirect symbolic correlation approach to unsegmented text recognition;background line detection with a stochastic model;estimating tracking sources and sinks;generic event detection in sports video using cinematic features;towards perceptual interface for visualization navigation of large data sets;coevolutionary computation for synthesis of recognition systems;mirror shape recovery from image curves and intrinsic parameters: rotationally symmetric and conic mirrors;parametric subpixel matchpoint recovery with uncertainty estimation: a statistical approach;and tracking random sets of vehicles in terrain.
In this paper, we propose a data driven approach to first-person vision. We propose a novel image matching algorithm, named Re-Search, that is designed to cope with self-repetitive structures and confusing patterns in...
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ISBN:
(纸本)9781424439942
In this paper, we propose a data driven approach to first-person vision. We propose a novel image matching algorithm, named Re-Search, that is designed to cope with self-repetitive structures and confusing patterns in the indoor environment. This algorithm uses state-of-art image search techniques, and it matches a query image with a two-pass strategy. In the first pass, a conventional image search algorithm is used to search for a small number of images that are most similar to the query image. In the second pass, the retrieval results from the first step are used to discover features that are more distinctive in the local context. We demonstrate and evaluate the Re-Search algorithm in the context of indoor localization, with the illustration of potential applications in object pop-out and data-driven zoom-in.
Future intelligent environments and systems may need to interact with humans while simultaneously analyzing events and critical situations. Assistive living, advanced driver assistance systems, and intelligent command...
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Future intelligent environments and systems may need to interact with humans while simultaneously analyzing events and critical situations. Assistive living, advanced driver assistance systems, and intelligent command-and-control centers are just a few of these cases where human interactions play a critical role in situation analysis. In particular, the behavior or body language of the human subject may be a strong indicator of the context of the situation. In this paper we demonstrate how the interaction of a human observer's head pose and eye gaze behaviors can provide significant insight into the context of the event. Such semantic data derived from human behaviors can be used to help interpret and recognize an ongoing event. We present examples from driving and intelligent meeting rooms to support these conclusions, and demonstrate how to use these techniques to improve contextual learning.
Facial aging has been only partially studied in the past and mostly in a qualitative way. This paper presents a novel approach to the estimation of facial aging aimed to the quantitative evaluation of the changes in f...
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Facial aging has been only partially studied in the past and mostly in a qualitative way. This paper presents a novel approach to the estimation of facial aging aimed to the quantitative evaluation of the changes in facial appearance over time. In particular, the changes both in face shape and texture, due to short-time aging, are considered. The developed framework exploits the concept of “distinctiveness” of facial features and the temporal evolution of such measure. The analysis is performed both at a global and local level to define the features which are more stable over time. Several experiments are performed on publicly available databases with image sequences densely sampled over a time span of several years. The reported results clearly show the potential of the methodology to a number of applications in biometric identification from human faces.
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