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Appearance based multi-object tracking (MOT) is a challenging task, specially in complex scenes where objects have similar appearance or are occluded by background or other objects. Such factors motivate researchers to propose effective trackers which should satisfy real-time processing and object trajectory recovery criteria. In order to handle both mentioned requirements, we propose a robust online...
Appearance based person re-identification in real-world video surveillance systems is a challenging problem for many reasons, including ineptness of existing low level features under significant viewpoint, illumination, or camera characteristic changes to robustly describe a person's appearance. One approach to handle appearance variability is to learn similarity metrics or ranking functions to implicitly...
Appearance based person re-identification is a challenging task, specially due to difficulty in capturing high intra-person appearance variance across cameras when inter-person similarity is also high. Metric learning is often used to address deficiency of low-level features by learning view specific re-identification models. The models are often acquired using a supervised algorithm. This is not...
Applications like content-based image indexing, automatic geocoding of businesses and real-time robotic navigation have generated research interest in the problem of text reading from natural images. This paper tackles the problem of character recognition which constitutes the last phase of the text detection and extraction pipeline. We employ the stroke width transform[12] used for the text detection...
Gesture recognition has recently generated significant research interest. It is primarily apprehensive on exploring the performance of human acumen. Visual understanding of hand gestures can help in attaining the simplicity and characteristic craved for Human Computer Interaction (HCI). Gesture recognition is effortless for human beings but a very challenging task when it comes to computers. To aid...
The task of understanding video content has seen great interest from computer vision community with the increase in camera based surveillance at grocery stores, airports, train stations, etc. What makes up a scene (objects) and what happens in the scene (actions) are two important dimensions of video understanding. In this work, we aim to identify both actions and objects in the video, however, we...
Human movements are important cues for recognizing human actions, which can be captured by explicit modeling and tracking of actor or through space-time low-level features. However, relying solely on human dynamics is not enough to discriminate between actions which have similar human dynamics, such as smoking and drinking, irrespective of the modeling method. Object perception plays an important...
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