Sharif Digital Repository

In this paper, intelligent traffic surveillance system as an important part of a smart resilient city is reviewed. The smart traffic control system is very important in improving the lifestyle by decreasing the traffic saturation and air pollution. Still, multi-camera vision is more helpful in implementing different automatic traffic surveillance systems. Apart from their superior features, existing multi-camera surveillance systems suffer from computational complexity and degraded accuracy. The main reason for these shortcomings arises from image processing errors. These errors depend on the image content and thus are not predictable. To overcome this shortage, three-dimensional (3D)... 

In this paper, a novel approach for foreground extraction has been proposed based on a popular three-dimensional imaging technique in optics, called integral imaging. In this approach, multiple viewpoint images captured from a three-dimensional scene are used to extract range information of the scene and effectively extract an object or a person, even in the presence of heavy occlusion. The algorithm consists of two parts: depth estimation and reconstruction of the targeted object at the estimated depth distance. Further processing of the resulting reconstructed image can lead to the detection of a face or a pedestrian in the scene, which may not otherwise be detectable due to partial... 

Tracking vehicles across nonoverlapping cameras is required by video-based intelligent transportation systems (ITS) to efficiently calculate traffic parameters; such as link travel times and origin/destination counts. In traffic monitoring applications, cameras are usually mounted far from each other to cover wide areas. As such, object features (i.e., color information, shape, and direction) change significantly from one camera to another. These space-time differences raise serious challenges on efficient tracking. In this paper, we have presented a probabilistic model to solve the multicamera tracking task in a network of disjoint view cameras, with attention paid on estimating the density... 

In this paper, a novel moving object modeling suitable for multicamera correspondence is introduced. Taking into consideration the color and motion features of foreground objects in each independent video stream, our method segments the existing moving objects and constructs a graph-based structure to maintain the relational information of each segment. Using such graph structures reduces our correspondence problem to a subgraph optimal isomorphism problem. The proposed method is robust against various resolutions and orientations of objects at each view. Our system uses the fuzzy logic to employ a human-like color perception in its decision making stage in order to handle color inconstancy... 

In this paper, we propose and compare various approaches of feature and decision fusion for human action classification in a multi-view framework. The key difference between the employed methods is in the nature of extracted features in each view and the stage we fuse data from all cameras to classify the activity. At the feature extraction stage we utilize three different methods. At the decision making stage, the features obtained by the cameras are combined in a single classifier, or a classifier for each camera produces a local decision which is combined with decisions from other cameras for a global decision. We have employed our method on a fall detection dataset, and all the fusion... 

Object handover as continually tracking an object across disjoint-view cameras is a necessary part of video-based monitoring systems. While having nonoverlapping cameras is a requirement for monitoring a wide area, there is no common 3D location that can be used to detect multiple views of the same object, in contrast with overlapping cameras. Appearance features play an important role for object handover in such camera networks. This paper focuses on modeling appearance features of moving vehicles by a new major color representation called codebook representation. Toward this end, in each frame, the k-means algorithm is used to cluster major colors of an object. In the subsequent frames, a...