Aimed at the shortcomings of the traditional video monitoring system, human detection method in intelligent video monitoring system was researched. This paper proposed a human detection method based on motion object extraction and head–shoulder feature to complete human detection and statistics in video image sequences. Firstly, background subtraction based on adaptive threshold was used to ext...

Object recognition in the video sequence or images is one of the sub-field of computer vision. Moving object recognition from a video sequence is an appealing topic with applications in various areas such as airport safety, intrusion surveillance, video monitoring, intelligent highway, etc. Moving object recognition is the most challenging task in intelligent video surveillance system. In this ...

Moving shadow detection is an important topic in computer vision applications, including video conference, vehicle tracking, and three-dimensional (3-D) object identification, and has been actively investigated in recent years. Because, in real world scenes, moving cast shadows may be detected as foreground object and plauge the moving objects segmentation. For example, in traffic surveillance ...

In this paper, we outline a moving object recognition system. A description is given of the whole system from the image acquisition through the preprocessing and feature extraction stages to the classiication of objects. We use Quadratic Neural Networks (QNN) to model the input data and then extract features from the model which are translation and rotation invariant. We have applied the idea t...

Detection of moving objects in a video sequence is a difficult task and robust moving object detection in video frames for video surveillance applications is a challenging problem. Object detection is a fundamental step for automated video analysis in many vision applications. Object detection in a video is usually performed by object detectors or background subtraction techniques. Frequently, ...

In this paper, we present a multiple active camera assignment for high fidelity 3D video of a moving object, mainly an acting human body. The camera system is made up of cameras with long focal length lenses for high resolution input images. However, such cameras can capture only partial views of the object. Our goal is to assign the camera set to the different parts of the moving object so as ...

The three-stage human brain memory model is incorporated into a multiagent coevolutionary process for finding the best match of the appearance of an object, and a memory-based multiagent coevolution algorithm for robust tracking the moving objects is presented in this paper. Each agent can remember, retrieve, or forget the appearance of the object through its own memory system by its own experi...

The paper proposes a way of parallel processing of SURF and Optical Flow for moving object recognition and tracking. The object recognition and tracking is one of the most important task in computer vision, however disadvantage are many operations cause processing speed slower so that it can’t do real-time object recognition and tracking. The proposed method uses a typical way of feature extrac...

Using stereo disparity or depth information to detect and track moving objects is receiving increasing attention in recent years. However, this approach suffers from some difficulties, such as synchronisation between two cameras and doubling of the image-data size. Besides, traditional stereo-imaging systems have a limited field of view (FOV), which means that they need to rotate the cameras wh...

When a flash is aligned with a moving object, subjects perceive the flash to lag behind the moving object. Two different models have been proposed to explain this "flash-lag" effect. In the motion extrapolation model, the visual system extrapolates the location of the moving object to counteract neural propagation delays, whereas in the latency difference model, it is hypothesized that moving o...