11631224
An Algorithm for Finding Parameter Dependent: Connected Components of Gray Images
In a previous work we have introduced the concept of a parameter-dependent connected component of grayscale images that takes into account both the gray values of the pixels and the di erences of the gray values of the neighboring pixels. This concept is a convenient tool to analyze or understand images at a higher level than the pixel level. In this paper, we describe an algorithm for nding the parameter-dependent components for a given image. We discuss di erent strategies used in the algorithm and analyze their e ects through the experimental results. Since the proposed algorithm is independent of the formation of the images, it can be used for the analysis of many types of images. The experimental results show that for some appropriate values of the parameters, the objects of an image may be represented by its parameter-dependent components reasonably well. Thus, the proposed algorithm provides us with the posibility of analyzing images further at the component level.
19740000
Color Image Segmentation Based on Parameter-Dependent Connected Components
A theory of a parameter-dependent connected components of gray images that takes into account both the gray values of the pixels and the differences of the gray values of the neighboring pixels has been introduced in a previous work. The concept of the parameter-dependent connected components has been applied to gray-scaled images for segmentation successfully. In this paper, the author investigates a method to apply the concept of the parameterdependent connected components to color images for segmentation.
58732767
Parameter-dependent connected component of gray images and image understanding, segmentation and stereo correspondence
43870484
On parameter-dependent connected components of gray images
Abstract We introduce a new definition of the connected components of gray images which takes into account both the gray values of the pixels and the differences of the gray values of the neighbouring pixels and which depends on two parameters, e and δ. We may adjust the values of the parameters for different types of images or in different levels of image analysis. We analyse a gray image in an intermediate level through the inter-relationships of its (e, δ) components rather than only in the pixel level.
9978380
Learning a discriminative hidden part model for human action recognition
We present a discriminative part-based approach for human action recognition from video sequences using motion features. Our model is based on the recently proposed hidden conditional random field (hCRF) for object recognition. Similar to hCRF for object recognition, we model a human action by a flexible constellation of parts conditioned on image observations. Different from object recognition, our model combines both large-scale global features and local patch features to distinguish various actions. Our experimental results show that our model is comparable to other state-of-the-art approaches in action recognition. In particular, our experimental results demonstrate that combining large-scale global features and local patch features performs significantly better than directly applying hCRF on local patches alone.
23190531
Algorithm for yield driven correction of layout
As the development of VLSI technique, the critical dimension of IC has become smaller than the exposure wavelength. Due to the diffraction and interaction of optical waves, deformations between the image on wafer and the feature on layout are undeniable. This results in bad performance or even invalid circuits of the chips. OPC is critical compensation technique to correct the deformations on wafer images. This work presents a layout correction and optimization algorithm called MOPC; it's a flexible and efficient core for the model-based OPC system. Since we divide the target features into different types before correction, the OPE between the target features and the environment features and the OPE between the neighboring segments of the inside feature are both considered during the correction.
9587091
Topology control for delay-constraint data collection in wireless sensor networks
Data collection is one of the most important operations in wireless sensor networks. Many practical applications require the real-time data transmission, such as monitoring, tracking, etc. In this paper, we import and define the topology control problem for delay-constraint data collection (TDDC), and then formalize this problem into an integer programming problem. As NP-Hardness of this problem, we present a load-aware power-increased topology control algorithm (namely LPTC) to heuristically solve the problem. The theoretical analysis shows that this algorithm can reach O(1)-approximation ratio for the linear networks. And we also analyze the impact of the delay-constraint on the worst-case for the planar networks. Moreover, this paper designs two localized algorithms, called as SDEL and DDEL, based on the area division for TDDC problem. The experimental results show that LPTC algorithm can save at least 17% power consumptions compared with HBH algorithm in many situations.
15156880
Adaptive Foreground and Shadow Detection in Image Sequences
This paper presents a novel method of foreground segmentation that distinguishes moving objects from their moving cast shadows in monocular image sequences. The models of background, edge information, and shadow are set up and adaptively updated. A Bayesian belief network is proposed to describe the relationships among the segmentation label, background, intensity, and edge information. The notion of Markov random field is used to encourage the spatial connectivity of the segmented regions. The solution is obtained by maximizing the posterior possibility density of the segmentation field.
18703752
Video editing based on object movement and camera motion
The advancement of computer technology makes video devices/equipments powerful and inexpensive, and thereby the number of applications that can effectively utilize digital videos is increasing.In this paper, the authors propose a new type of video editing, which is based on the movement of objects. A video shot is automatically edited so that the selected objects are placed and kept at the center of the frames to make the resultant video more attractive. Ideally this is interpreted as applying pan, tilt, and/or zoom operations into a source video as post-conditions in video editing. Implementation issues for realization of this facility are also presented in this paper.