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In this paper we analyze the neural progenitor cells in a time-lapse sequence to find position, shape, motility and ancestor of each cell in the frame. Because of the complex nature of cells, the ability to distinguish a cell from the background of an image for automatic quantification remains a challenging task. By using morphological techniques we are able to make a better selection of blob-like...
We present an extension of a neuro-dynamic object recognition system that combines bottom-up recognition of matching patterns and top-down estimation of pose parameters in a recurrent loop. It is extended by an active foveal vision system. Adding the active vision component is easily integrated within the architecture and improves the recognition rate on previous experiments on the COIL-100 database...
Due to affecting by the human body irregular movement or other appendage while detecting human traffic in the channel, the accuracy of flow calculation system is unsatisfactory. We propose a new robust way to detect and count walking persons in channel areas, which mainly includes four aspects: (1) to avoid the human bodies being blocked mutually by vertically fixed monochromatic cameras; (2) to determine...
Active Appearance Model (AAM) based face tracking has advantages of accurate alignment, high efficiency, and effectiveness for handling face deformation. However, AAM suffers from the generalization problem and has difficulties in images with cluttered backgrounds. In this paper, we introduce two novel constraints into AAM fitting to address the above problems. We first introduce a temporal matching...
In this paper we propose a novel method for object tracking in video images. The method is based on image segmentation and pattern matching. All moving and still objects in video images can be detected accurately with the help of efficient image segmentation techniques. We propose a hybrid algorithm for image segmentation using the notion of Particle Swarm Optimization (PSO) and Fuzzy-C-Means (FCM)...
In this paper, a semi-automatic road extraction algorithm is proposed. The algorithm starts from a Euclidean distance transform to convert the original remote sensing image into a distance image, which presents all roads in the darker color and can be used as the input image for further process. Then, the contrast of the distance image is enhanced and the skeletons of roads are found. Following these...
In this paper, we propose an effective approach for tracking distribution of objects. The approach uses a competition between a tracked objet and background distributions using active contours. Only the segmentation of the object in the first frame is required for initialization. We evolve the object contour by assigning pixels in a fashion that maximizes the likelihood of the object versus the background...
This paper describes developing of an occlusion robust tracking algorithm of pedestrians in the panning images by the combination between the S-T MRF model and pattern recognition methods of Snakes and HOG classifier. Tracking in panning images would extend the field of view of single camera. In addition, an algorithm to match pedestrians between cameras that have overlapping area with each other...
Performance evaluation of object tracking systems is typically performed after the data has been processed, by comparing tracking results to ground truth. Whilst this approach is fine when performing offline testing, it does not allow for real-time analysis of the systems performance, which may be of use for live systems to either automatically tune the system or report reliability. In this paper,...
This paper presents approach for an automated surveillance system which performs human detection and tracking across multiple non-overlapping cameras. Emphasis is put at single camera level where motion based segmentation is achieved using optical flow estimation. Feature matching and region-based shape descriptors are used for tracking. The proposed approach then extends feature and region-based...
As dissolve is the most common gradual shot transition, dissolve detection plays an important role in video segmentation which is the fundamental step for efficient video indexing and retrieval. However, the existing detection methods easily confuse dissolve with camera motion or object motion when using global features. Besides, when using local features' change tendency, they can' t get accurate...
We propose a novel motion analysis algorithm by using the mean-shift segmentation and motion estimation technique. Mean shift algorithm is frequently used to extract objects from video according to its efficiency and robustness of non-rigid object tracking. For diminishing the computational complexity in searching process, an efficient block matching algorithm: cross-diamond-hexagonal search algorithm...
Most approaches to vehicle tracking have adopted a single calibrated camera for the task, which leads to an under-conditioned problem. We present a surveillance system for on-line vehicle tracking based on two cameras and structure from motion (SfM). Our surveillance system starts by tracking feature points. A novel matching scheme is proposed that allows a subset of feature points to be corresponded...
The novel method of obtaining cellspsila electrorotation motion parameters through electrorotation test was proposed. Firstly, constructing the cell edge detection algorithm to locate edges, then, the ring window template was used to split every single cell from multicellular images by means of template matching scheme. Feature point tracking and cross-correlation tracking algorithms for cell rotation...
Two challenge problems in tracking objects in video are object segmentation and matching. Most previous methods can work with some user-specific control. In this paper, we will propose an adaptive algorithm for colour object tracking in video sequences based on background subtraction and image matching by using multiresolution critical point filter (CPFs). Which the background subtraction segment...
Aiming at improving the performance of non-rigid object tracking in video sequences acquired by a stationary camera, an effective method based on the adaptive color segmentation and object part model was presented. In this work, we modeled background and obtained the foreground blobs with an effective adaptive background updating method based on Gaussian mixture model (GMM), and then the regions in...
In this paper an efficient method of small object localization is proposed that integrates detection and tracking. The system is initialized using a strong detector and then it locates the object over time using a weak detector and a temporal tracker. Both of strong and weak detectors are based on foreground-background segmentation. The strong detector is created from shape analysis of foreground...
This paper presents a novel speech driven accurate realistic visual speech synthesis approach. Firstly, an audio visual instance database is built for different viseme context combinations, i.e. diviseme units, using 100 audio visual speech sentences of a female speaker. Then a diviseme instance selection algorithm is introduced to choose the optimal diviseme instances for the viseme contexts in the...
A novel three-stage framework for object tracking under stationary background conditions is proposed in this paper. The first stage uses an attention based method to extract motion information. The second stage then applies a region growing and matching technique to motion vectors to obtain motion segmentation. Finally the moving objects are tracked based on the displacements of region centroids....
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