Most algorithms for real-time tracking of deformable shapes provide sub-optimal solutions for a suitable energy minimization task: The search space is typically considered too large to allow for globally optimal solut...
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Most algorithms for real-time tracking of deformable shapes provide sub-optimal solutions for a suitable energy minimization task: The search space is typically considered too large to allow for globally optimal solutions. In this paper we show that - under reasonable constraints on the object motion - one can guarantee global optimality while maintaining real-time requirements. The problem is cast as finding the optimal cycle in a graph spanned by the prior template and the image. The underlying combinatorial algorithm is implemented on state-of-the-art graphics hardware. Solutions on FPGAs are conceivable. Experimental results demonstrate long-term tracking of cars in real-time, while coping with challenging weather conditions. In particular, we show that the proposed tracking algorithm is highly robust to illumination changes and that it outperforms local tracking methods such as the level set method.
Processing a video stream to segment foreground objects from the background is a critical first step in many computervision applications. Background subtraction (BGS) is a commonly used technique for achieving this s...
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In this paper, we focus on the number of solution for the Perspective-Three-point problem (P3P) in some geometrical constraints of 3 points, which is a common problem in applied mathematics and computervision. We use...
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ISBN:
(纸本)9783540874409
In this paper, we focus on the number of solution for the Perspective-Three-point problem (P3P) in some geometrical constraints of 3 points, which is a common problem in applied mathematics and computervision. We use Wu's zero decomposition method to find a complete triangular decomposition of a practical configuration for the P3P problem. By the Wu's method, we also obtain some sufficient conditions under which there are multi-solution for the P3P problem.
Network-on-Chip (NoC) is a precious approach to handle huge number of transistors by virtue of technology scaling to lower than 50nm. Virtual channels have been introduced in order to improve the performance according...
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ISBN:
(纸本)9781424442331
Network-on-Chip (NoC) is a precious approach to handle huge number of transistors by virtue of technology scaling to lower than 50nm. Virtual channels have been introduced in order to improve the performance according to a timing multiplexing concept in each physical channel. The incremental effect of virtual channels on power consumption has been shown in literatures. The issue of power saving has always been controversial to many designers. In this paper, we introduce a new technique which tries to adaptively mange the number of virtual channels in order to reduce the power consumption while not degrading the performance of the network without any reconfiguration. Our experimental results show the efficiency of our method in a torus topology under different traffic models and Duato routing algorithm with 49% and 30% power saving in the best and worst conditions, respectively.
One of the major problems remaining in tracking is occlusion handling. This paper presents a system for exactly this. A human model is defined and each body part is represented by a number of features. For each new im...
While global methods for matching shapes to images have recently been proposed, so far research has focused on small deformations of a fixed template. In this paper we present the first global method able to pixel-acc...
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While global methods for matching shapes to images have recently been proposed, so far research has focused on small deformations of a fixed template. In this paper we present the first global method able to pixel-accurately match non-rigidly deformable shapes across images at amenable run-times. By finding cycles of optimal ratio in a four-dimensional graph - spanned by the image, the prior shape and a set of rotation angles - we simultaneously compute a segmentation of the image plane, a matching of points on the template to points on the segmenting boundary, and a decomposition of the template into a set of deformable parts. In particular, the interpretation of the shape template as a collection of an a priori unknown number of deformable parts - an important aspect of higher-level shape representations - emerges as a byproduct of our matching algorithm. On real-world data of running people and walking animals, we demonstrate that the proposed method can match strongly deformed shapes, even in cases where simple shape measures and optic flow methods fail.
Recognizing people in images is one of the foremost challenges in computervision. It is important to remember that consumer photography has a highly social aspect. The photographer captures images not in a random fas...
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Recognizing people in images is one of the foremost challenges in computervision. It is important to remember that consumer photography has a highly social aspect. The photographer captures images not in a random fashion, but rather to remember or document meaningful events in her life. The culture of the society of which the photographer is a part provides a strong context for recognizing the content of the captured images. We demonstrate one aspect of this cultural context by recognizing people from first names. The distribution of first names chosen for newborn babies evolves with time and is gender-specific. As a result, a first name provides a strong prior for describing the individual. Specifically, we use the U.S. Social Security Administration baby name database to learn priors for gender and age for 6693 first names. Most face recognition methods do not even consider the name of the individual of interest, or the name is treated merely as an identifier that provides no information about appearance. In contrast, we combine image-based gender and age classifiers with the cultural context information provided by first names to recognize people with no labeled examples. Our model uses image-based age and gender estimates for assigning first names to people and in turn, the age and gender estimates are improved.
This paper presents a general framework for live video analysis. The activities of surveillance subjects are described using a spatio-temporal vocabulary learned from recurrent motion patterns. The repetitive nature o...
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In this paper we present parallel implementations of some representative low level vision algorithms on a cluster of workstations. These include convolution operation and the image restoration algorithm using Markov r...
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Tracking humans in an indoor environment is an essential part of surveillance systems. vision based and mirophone array based trackers have been extensively researched in the past. Audio-visual tracking frameworks hav...
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