In this paper, we propose a novel framework for behaviors recognition and detection of certain types of abnormal behaviors, capable of achieving high detection rates on a variety of real-life scenes. The new proposed approach here is a combination of the location based methods and the object based ones. First, a novel approach is formulated to use optical flow and binary motion video as the loc...

Previous work on novel object detection considers zero or few-shot settings where none few examples of each category are available for training. In real world scenarios, it is less practical to expect that ‘all’ the classes either unseen have few-examples. Here, we propose a more realistic setting termed ‘Any-shot detection’, totally and categories can simultaneously co-occur during inference. ...

multiple people detection and tracking is a challenging task in real-world crowded scenes. in this paper, we have presented an online multiple people tracking-by-detection approach with a single camera. we have detected objects with deformable part models and a visual background extractor. in the tracking phase we have used a combination of support vector machine (svm) person-specific classifie...

Multiple people detection and tracking is a challenging task in real-world crowded scenes. In this paper, we have presented an online multiple people tracking-by-detection approach with a single camera. We have detected objects with deformable part models and a visual background extractor. In the tracking phase we have used a combination of support vector machine (SVM) person-specific classifie...