Tools, techniques, datasets and application areas for object detection in an image: a review

• Published in: Multimedia tools and applications Vol. 81; no. 27; pp. 38297 - 38351
• Main Authors: Kaur, Jaskirat, Singh, Williamjeet
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.11.2022; Springer Nature B.V
• Subjects: Annotations; Artificial neural networks; Biometrics; Classification; Computer Communication Networks; Computer Science; Computer vision; Data Structures and Information Theory; Datasets; Literature reviews; Localization; Multimedia; Multimedia Information Systems; Object recognition; Optimization; Performance evaluation; Scientific papers; Special Purpose and Application-Based Systems; Surveillance; Deep learning; Computer vision; Dataset; Object detection
• ISSN: 1380-7501; 1573-7721
• DOI: 10.1007/s11042-022-13153-y

Object detection is one of the most fundamental and challenging tasks to locate objects in images and videos. Over the past, it has gained much attention to do more research on computer vision tasks such as object classification, counting of objects, and object monitoring. This study provides a detailed literature review focusing on object detection and discusses the object detection techniques. A systematic review has been followed to summarize the current research work’s findings and discuss seven research questions related to object detection. Our contribution to the current research work is (i) analysis of traditional, two-stage, one-stage object detection techniques, (ii) Dataset preparation and available standard dataset, (iii) Annotation tools, and (iv) performance evaluation metrics. In addition, a comparative analysis has been performed and analyzed that the proposed techniques are different in their architecture, optimization function, and training strategies. With the remarkable success of deep neural networks in object detection, the performance of the detectors has improved. Various research challenges and future directions for object detection also has been discussed in this research paper.