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This article is concerned with on-line counting of harmful insects of certain species in videos in the framework of in situ video-surveillance that aims at the early detection of prominent pest attacks in greenhouse crops. The video-processing challenges that need to be coped with concern mainly the low spatial resolution and color contrast of the objects of interest in the videos, the outdoor issues...
In this paper, we propose a novel appearance-based method for person re-identification, that condenses a set of frames of the same individual into a highly informative signature, called Histogram Plus Epitome, HPE. It incorporates complementary global and local statistical descriptions of the human appearance, focusing on the overall chromatic content, via histograms representation, and on the presence...
This paper proposes an automatic and robust method to detect and recognize the abandoned objects for video surveillance systems. Two Gaussian Mixture Models(Long-term and Short-term models) in the RGB color space are constructed to obtain two binary foreground masks. By refining the foreground masks through Radial Reach Filter (RRF) method, the influence of illumination changes is greatly reduced...
In this paper, we evaluate several low dimensional color features for object retrieval in surveillance video. Previous work in object retrieval in surveillance has been hampered by issues in low resolution, poor segmentation, pose and lighting variations and the cost of retrieval. To overcome these difficulties, we restrict our analysis to alarm-based vehicle detection and as a consequence, we restrict...
In this paper a system for autonomous video surveillance in relatively unconstrained environments is described. The system consists of two principal phases: object detection and object tracking. An adaptive background subtraction, together with a set of corrective algorithms, is used to cope with variable lighting, dynamic and articulate scenes, etc. The tracking algorithm is based on a matrix representation...
This paper describes an approach to segment and locate people in crowded scenarios with application to a surveillance system for airport dependencies. To obtain robust operation, the system analyzes a variety of visual cues -color, motion and shape- and integrates them optimally. A general method for automatic inference of optimal cue integration rules is presented. This schema, based on supervised...
This paper presents a novel method for reflection removal in the context of an object detection system. The method is based on chromatic properties of the reflections and does not require a geometric model of the objects. An experimental evaluation of the proposed method has been performed on a large database, showing its effectiveness.
Vision algorithms face many challenging issues when it comes to analyze human activities in video surveillance applications.For instance, occlusions makes the detection and tracking of people a hard task to perform. Hence advanced and adapted solutions are required to analyze the content of video sequences. We here present a people detection algorithm based on a hierarchical tree of Histogram of Oriented...
This paper proposes a novel method for tracking failure detection. The detection is based on the Forward-Backward error, i.e. the tracking is performed forward and backward in time and the discrepancies between these two trajectories are measured. We demonstrate that the proposed error enables reliable detection of tracking failures and selection of reliable trajectories in video sequences. We demonstrate...
This paper presents a complete system for accurately and efficiently counting vehicles in a highway surveillance video. The proposed approach employs vehicle detection and tracking modules. In the detection module, an automatically trained binary classifier detects vehicles while providing robustness against view-point, poor quality videos and clutter. Efficient tracking is then achieved by a simplified...
In many surveillance systems there is a requirement to determine whether a given person of interest has already been observed over a network of cameras. This paper presents two approaches for this person re-identification problem. In general the human appearance obtained in one camera is usually different from the ones obtained in another camera. In order to re-identify people the human signature...
This paper presents a novel disparity map refinement method and vision based surveillance framework for the task of detecting objects of interest in dynamic outdoor environments from two stereo video sequences taken at different times and from different viewing angles by a mobile camera platform. The proposed framework includes several steps, the first of which computes disparity maps of the same...
Text frame classification is needed in many applications such as event identification, exact event boundary identification, navigation, video surveillance in multimedia etc. To the best of our knowledge, there are no methods reported solely dedicated to text frame classifications so far. Hence this paper presents a new approach to text frame classification in video based on capturing local observable...
In this paper an improved real time algorithm for detecting pedestrians in surveillance video is proposed. The algorithm is based on people appearance and defines a person model as the union of four models of body parts. Firstly, motion segmentation is performed to detect moving pixels. Then, moving regions are extracted and tracked. Finally, the detected moving objects are classified as human or...
Background subtraction of video sequences is mainly regarded as a solved problem. However, no complete benchmark about Background Subtraction Algorithms (BSA) has been established, with ground truth and associated quality measures. One of the reasons is that such comparative study needs annotated datasets. In this article, we propose a BSA evaluation dataset built from realistic synthetic image and...
This paper presents a full motion detection system with post-processing applied to video surveillance. Motion detection is performed based on background subtraction (BGS). Our purpose is to show how an appropriate post-processing improves segmentation result provided by a BGS technique from the literature. First, BGS is performed using the codebook algorithm. Post-processing is then applied on the...
The issue of privacy protection in video surveillance has drawn a lot of interest lately. However, thorough performance analysis and validation is still lacking, especially regarding the fulfillment of privacy-related requirements. In this paper, we put forward a framework to assess the capacity of privacy protection solutions to hide distinguishing facial information and to conceal identity. We then...
In this paper, we propose a novel background subtraction approach in order to accurately detect moving objects. Our method involves three important proposed modules: a block alarm module, a background modeling module, and an object extraction module. Our proposed block alarm module efficiently checks each block for the presence of either moving object or background information. This is accomplished...
A multimedia surveillance system aims to provide security and safety of people in a monitored space. However, due to the nature of surveillance, privacy-sensitive information, such as face, gait and other physical parameters based on the captured media from multiple sensors, can be revealed without the concern of the people. This is a major concern in recent days. Therefore, it is desirable to have...
This paper proposes an obstacle detection system for the purpose of preventing accidents at level crossings. In order to avoid the limits of already proposed technologies, this system uses stereo cameras to detect and localize multiple targets at the level crossing. In a first step, a background subtraction module is performed using the Color Independent Component Analysis (CICA) technique which allows...
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