Density independent hydrodynamics model for crowd coherency detection

Abstract

We propose density independent hydrodynamics model (DIHM) which is a novel and automatic method for coherency detection in crowded scenes. One of the major advantages of the DIHM is its capability to handle changing density over time. Moreover, the DIHM avoids oversegmentation and thus achieves refined coherency detection. In the proposed DIHM, we first extract a motion flow field from the input video through particle initialization and dense optical flow. The particles of interest are then collected to retain only the most motile and informative particles. To represent each particle, we accumulate the contribution of each particle in a weighted form, based on a kernel function. Next, the smoothed particle hydrodynamics (SPH) is adopted to detect coherent regions. Finally, the detected coherent regions are refined to remove the effects of oversegmentation. We perform extensive experiments on three benchmark datasets and compare the results with 10 state-of-the-art coherency detection methods. Our results show that DIHM achieves superior coherency detection and outperforms the compared methods in both pixel level and coherent region level average particle error rates (PERs), average coherent number error (CNE) and F-score.

Estimation of linear motion in dense crowd videos using Langevin model

“…The method has been compared with methods proposed in (Ali and Shah, 2007), Accuracy Rath Yatra F 1 F 2 F 3 F 1 +F 2 F 2 +F 3 F 1 +F 3 F 1 +F 2 +F 3 Figure 10: Ablation experiment results conducted on the force model proposed in (7) (Santoro et al, 2010), (Zhou et al, 2014),and (Ullah et al, 2017), respectively.…”

“…In (Ullah, Uzair, Ullah, Khan, Ahmad, and Khan, 2017), a density independent hydrodynamics model (DIHM) for coherency detection in crowded scenes, has been proposed. The method has the capability to handle changing density over time.…”

“…• It has also been understood that, none of the existing methods such as (Ali and Shah, 2007) or (Ullah, Uzair, Ullah, Khan, Ahmad, and Khan, 2017) address the movement as random particles in the fluid. This has been one of the key motivations behind the idea presented in this paper.…”

A survey of advances in vision-based vehicle re-identification

“…In modern public transportation systems, video surveillance for traffic control and security plays a significant role. Therefore, obtaining accurate traffic information is increasingly in demand for many reasons including collection of statistical data de Dios OrtAozar and Willumsen (2011), controlling traffic signals and flows Lämmer and Helbing (2008) Ullah and Conci (2013) Khan et al (2016) Ullah et al (2017), law enforcement Vishnu et al (2017), Maaloul et al (2017) Saghafi et al (2012) Hsu et al (2013), smart transportation , accident detection Ullah et al (2015), and urban computing Zheng et al (2014). In traffic areas, many surveillance cameras are already installed.…”

Characterizing Human Behaviours Using Statistical Motion Descriptor

“…Automatic recognition of human actions play the importance role and is the most dominating research topic in computer vision research [1], [2], [3]. It has a wide range of application in automated surveillance [7], [8], [9] [10], human computer interaction [4], [5], [6], and video indexing [11], [12], [13] and video retrieval [14], [15], [16]. Human perform action for a specific purpose.…”