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Detecting, tracking, and identifying horses across heterogeneous videos

Lievense, M.M. (2021) Detecting, tracking, and identifying horses across heterogeneous videos.

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Abstract:Being able to localize unique subjects across a collection of heterogeneous videos in an unsupervised manner is a challenging task. A task that humans are able to perform quite accurately. We can analyse and understand scenes, easily follow subjects through a video, and are able to re-identify lost subjects based on their appearance. Implementing these skills into a computer system crosses various computer vision and artificial intelligence fields. State of the art applications have been created for use cases where humans are the subject. This thesis aims to tackle the research question: Which state of the art applications can be utilized to extract the information about the occurrence of unique subjects from heterogeneous videos and what are the limitations of these existing applications. Based on these applications and limitations, a pipeline was created with YoloV4+DeepSORT and FairMOT that can detect, track and re-identify, adapted for non-human subjects to finally output the desired information. The subject type used in this thesis are horses, however, this thesis is applicable to any other subject type with a suitable training set. The two limitations that were found in the re-identification task are 1) the incapability to extract long-term information from horses resulting in insufficient accuracy when attempting to re-identify subjects and 2) the online method of tracking resulting in undesired identify transfers. Suggestions on how to improve these limitations are given. The final pipeline was able to detect 93\% of the horses within the evaluation frames and was able to minimize the number of identity transfers to 5 within the evaluation fragments.
Item Type:Essay (Bachelor)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:54 computer science
Programme:Advanced Technology BSc (50002)
Link to this item:http://purl.utwente.nl/essays/86808
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