Pregled bibliografske jedinice broj: 1212619
A new approach to dominant motion pattern recognition at the macroscopic crowd level
A new approach to dominant motion pattern recognition at the macroscopic crowd level // Engineering applications of artificial intelligence, 116 (2022), 105387, 18 doi:10.1016/j.engappai.2022.105387 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 1212619 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
A new approach to dominant motion pattern recognition at the macroscopic crowd level
Autori
Matković, Franjo ; Ivašić-Kos, Marina ; Ribarić, Slobodan
Izvornik
Engineering applications of artificial intelligence (0952-1976) 116
(2022);
105387, 18
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
Asymmetric potential function Dominant motion pattern Macroscopic crowd level Meta-tracklet Particle advection Wave function
Sažetak
Automatic analysis and the recognition and prediction of the behaviour of large-scale crowds in video-surveillance data is a research field of paramount importance for the security of modern societies. It serves to predict and help prevent disasters in public places where crowds of people gather. The paper proposes a novel method for generating meta-tracklets and recognition of dominant motion patterns as a basis for automatic crowd behaviour analysis at the macroscopic level, where a crowd is treated as an entity. The basic characteristic of macroscopic crowd scenes is that it is impossible to detect and track individuals in the scene. The idea of the method proposed in this paper is to recognize dominant crowd motion patterns, by avoiding time-consuming and error-sensitive crowd segmentation, crowd tracking and detection of regions of interest. Thus, the process of determining dominant motion patterns and recognizing crowd behaviour is accelerated. The method is inspired by a quantum mechanical approach. It combines a set of particles, which are considered as particles in quantum mechanics, tracklets of particles’ advection in a video clip, and the interaction of wave functions spread out from particle positions. A wave function is expressed in the form of an asymmetric potential function. Peaks of the wave field define the most probable particle flow, which defines a meta-tracklet. Dominant motion patterns are recognized by applying the functions of fuzzy predicates, which represent a combination of common-sense and human expert knowledge about crowd motions, to the meta-tracklets. The experimental results of the proposed method are presented for a subset of UCF dataset and AGORASET crowd simulation videos and have shown promising results in dominant motion pattern recognition.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
POVEZANOST RADA
Projekti:
HRZZ-IP-2018-01-7619 - Pristup utemeljen na znanju za analizu mnoštva ljudi u nadzornim sustavima (KACAVIS) (Ribarić, Slobodan, HRZZ ) ( CroRIS)
NadSve-Sveučilište u Rijeci-uniri-drustv-18-222 - Automatsko raspoznavanje sportskih tehnika kod mladih sportaša i rekreativaca u svrhu usvajanja motoričkih vještina i usavršavanje stila (Ivašić Kos, Marina, NadSve - Natječaj za dodjelu sredstava potpore znanstvenim istraživanjima na Sveučilištu u Rijeci za 2018. godinu - projekti iskusnih znanstvenika i umjetnika) ( CroRIS)
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus