Contour Of Moving Object Research Articles

Analysis and Optimization of Computer Trajectory Based on Compound Eye Vision System

With the rapid development of science and technology, people have higher and higher requirements for target detection technology, which requires us to solve the disadvantages of traditional cameras, such as the difficulty of panoramic photography and continuous tracking motion. However, compound eye insects have a visual system composed of fewer neurons, which can achieve rapid detection and capture of objects of interest. Therefore, based on the principle of compound eye vision, a bionic compound eye panoramic detection system is designed in this paper, which can realize panoramic real-time detection through multiple sub eye cameras. Through the compound eye vision system, we can accurately locate the pan tilt controller, which can provide a comprehensive panoramic motion image. Through the principle of automatic windowing, we can acquire the image of moving area by multi-layer window. Then, through the relevant image processing methods, such as binarization, median filtering, spatial filtering, moving object detection, edge detection and other methods, we can get a relatively clear moving object contour and trajectory analysis, which can achieve full field of view, high sensitivity detection and tracking.

Research and Implementation of Moving Object Contour Extraction Algorithm Based on GPU

In this paper, frame differential method will be used to detect moving targets in a static background video file, and pre-contour can be obtained by binarizing the detected targets . However,, the result are not what was expected, so the expansion and corrosion of mathematical morphology are used to extract the final contour of moving targets. in the progress of dealing with massive data , mathematical morphology is not good enough to achieve the need of the real-time in video surveillance. Considering the dilation and erosion is a kind of parallel processing operations, in order to improve the speed of mathematical morphology operations, this paper offers detailed implementation process of the dilation algorithm for parallel computing on GPU. Experimental results showed that GPU parallel processing on mathematical morphology algorithm faster than the CPU serial processing.

고정 카메라에서의 시공간적 경계 정보를 이용한 이동 객체 윤곽선 검출 방법

In this paper, we propose a new method for detection moving object contour using spatial and temporal edge. In general, contour pixels of the moving object are likely present around pixels with high gradient value along the time axis and the spatial axis. Therefore, we can detect the contour of the moving objects by finding pixels which have high gradient value in the time axis and spatial axis. In this paper, we introduce a new computation method, termed as temporal edge, to compute an gradient value along the time axis for any pixel on an image. The temporal edge can be computed using two input gray images at time  and    using the Sobel operator. Temporal edge is utilized to detect a candidate region of the moving object contour and then the detected candidate region is used to extract spatial edge information. The final contour of the moving object is detected using the combination of these two edge information, which are temporal edge and spatial edge, and then the post processing such as a morphological operation and a background edge removing procedure are applied to remove noise regions. The complexity of the proposed method is very low because it dose not use any background scene and high complex operation, therefore it can be applied to real-time applications. Experimental results show that the proposed method outperforms the conventional contour extraction methods in term of processing effort and a ghost effect which is occurred in the case of entropy method.

A novel fast moving object contour tracking algorithm

If a somewhat fast moving object exists in a complicated tracking environment, snake’s nodes may fall into the inaccurate local minima. We propose a mean shift snake algorithm to solve this problem. However, if the object goes beyond the limits of mean shift snake module operation in successive sequences, mean shift snake’s nodes may also fall into the local minima in their moving to the new object position. This paper presents a motion compensation strategy by using particle filter; therefore a new Particle Filter Mean Shift Snake (PFMSS) algorithm is proposed which combines particle filter with mean shift snake to fulfill the estimation of the fast moving object contour. Firstly, the fast moving object is tracked by particle filter to create a coarse position which is used to initialize the mean shift algorithm. Secondly, the whole relevant motion information is used to compensate the snake’s node positions. Finally, snake algorithm is used to extract the exact object contour and the useful information of the object is fed back. Some real world sequences are tested and the results show that the novel tracking method have a good performance with high accuracy in solving the fast moving problems in cluttered background.

Constructive Brain Processes in Motion Perception

Bistable perceptions allow the dissociation of perception- from stimulus-related neural processes. We investigated the neural mechanisms underlying bistable apparent motion (AM) perception using functional magnetic resonance imaging (fMRI). In a first set of experiments, we asked how perceptual reversals during bistable AM are coded in extrastriate visual areas. We assessed event-related activations associated with perceptual reversals during continuous presentation of two different ambiguous AM stimuli, the 'spinning wheel illusion' and the 'dynamic dot quartet' (see figure). Contrasting with previous studies that used bistable paradigms involving objects or faces, we detected no reversal-related activations in ventral extrastriate regions, but instead in the human motion complex (hMT+/V5) with both ambiguous AM stimuli used. This suggests an attribute-specific coding of perceptual reversals in extrastriate visual cortex. In the spinning wheel illusion but not in the dynamic dot quartet, we observed additional reversal-related activations in the „kinetic occipital“ area, which has been implicated in the processing of kinetic contours. Since the spinning wheel stimulus, in contrast to the dynamic dot quartet, evokes the impression of a moving object contour in front of a stationary background, the different response patterns indicate a fine-tuning of reversal-related activations to stimulus features. In a second set of experiments, we were interested in the neural correlates of 'correspondence', which refers to the question of how the visual system determines which object in one frame corresponds to which object in the next in ambiguous AM displays. To investigate the influence of intrinsic object properties on the path of AM, we used dynamic dot quartets with differences in color or luminance serving as correspondence cues. We observed a suppression of neural activity in the calcarine cortex (V1) whenever perceived AM paths violated color and luminance cues. In contrast, when AM paths matched the correspondence cues, V1 activity was the same as during perception of uncued displays. This finding might reflect regulatory mechanisms that flexibly gate early visual feature processing in accord with an overruling perceptual decision. Taken together, our findings indicate that reversal-related activation patterns in bistable visual perception are not only attribute-specific but depend on stimulus characteristics in a finely tuned way suitable to encode perceptual content in the absence of sensory input changes. Moreover, perceptual decisions seem to be associated with adjustments of activity levels at early visual processing stages.