Deep Counting Models and their Use for Person Detection

Sanjukta Ghosh (Autor)

Buch | Softcover

219 Seiten

2020
Dr. Hut (Verlag)
978-3-8439-4342-0 (ISBN)

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The focus of this thesis is to use deep learning-based approaches for person detection in real scenarios with challenges like partially occluded or distant persons that appear small along with the lack of availability of training data and annotations. To achieve this, deep counting models (DCM) are proposed as a novel and fundamental mechanism. A DCM is a deep model for counting a specific category of objects. In this thesis, the theoretical aspect of such models is motivated using the Information Bottleneck principle. A systematic approach to train and create deep models for counting using synthetic images is outlined. An extensive analysis of DCMs is done and found to have properties useful for detection. The insights gained are used to evolve various person detection techniques based on the deep counting model.

Erscheinungsdatum	25.02.2020
Reihe/Serie	Ingenieurwissenschaften
Verlagsort	München
Sprache	englisch
Maße	148 x 210 mm
Gewicht	336 g
Themenwelt	Technik
Schlagworte	Deep Counting Model • Deep learning • person detection
ISBN-10	3-8439-4342-7 / 3843943427
ISBN-13	978-3-8439-4342-0 / 9783843943420
Zustand	Neuware