This paper proposes a new indoor people detection and tracking system using millimeter-wave (mmWave) radar sensor. Firstly, systematic approach for is presented—a static clutter removal algorithm used removing mmWave data’s points. Two efficient clustering algorithms are to cluster identify in scene. The recursive Kalman filter with data association track multiple simultaneously. Secondly, fast...

We describe a method that can detect specific human behaviors even in crowded surveillance video scenes. Our developed system recognizes specific behaviors based on the trajectories created by detecting and tracking people in a video. It detects people using an HOG descriptor and SVM classifier, and it tracks the regions by calculating the two-dimensional color histograms. Our system identifies...

Tracking a moving person is challenging because a person’s appearance in images changes significantly due to articulation, viewpoint changes, and lighting variation across a scene. And different people appear differently due to numerous factors such as body shape, clothing, skin color, and hair. In this thesis, a multi-cue tracking technique is introduced that uses prior information about the 2...

—We introduce a novel, accurate and practical system for real-time people tracking and identification. We used a Kinect V2 sensor for tracking that generates a body skeleton for up to six people in the view. We perform identification using both Kinect and passive RFID, by first measuring the velocity vector of person's skeleton and of their RFID tag using the position of the RFID reader antenna...

Multi-People Tracking in an open-world setting requires a special effort in precise detection. Moreover, temporal continuity in the detection phase gains more importance when scene cluttering introduces the challenging problems of occluded targets. For the purpose, we propose a deep network architecture that jointly extracts people body parts and associates them across short temporal spans. Our...

We propose a method for real-time people tracking using multiple cameras. The particle filter framework is known to be effective for tracking people, but most of existing methods adopt only simple perceptual cues such as color histogram or contour similarity for hypothesis evaluation. To improve the robustness and accuracy of tracking more sophisticated hypothesis evaluation is indispensable. W...

Recent investigations have shown the advantages of keeping multiple hypotheses during visual tracking. In this paper we explore an alternative method that keeps just a single hypothesis per tracked object for computational e ciency, but displays robust performance and recovery from error by employing continuous detection during tracking. The method is implemented in the domain of people-trackin...

People were given highly constrained low budgets of mate dollars to allocate across various characteristics pertaining to their ideal partners and to their ideal selves for longand short-term mating. First, results replicated findings from Li et al. (2002) and Li & Kenrick (2006). For ideal long-term mates, men prioritized physical attractiveness and women prioritized social status. For ideal s...