  Smart retail stores are becoming the fact of our lives. Several computer
vision and sensor based systems are working together to achieve such a complex
and automated operation. Besides, the retail sector already has several open
and challenging problems which can be solved with the help of pattern
recognition and computer vision methods. One important problem to be tackled is
the planogram compliance control. In this study, we propose a novel method to
solve it. The proposed method is based on object detection, planogram
compliance control, and focused and iterative search steps. The object
detection step is formed by local feature extraction and implicit shape model
formation. The planogram compliance control step is formed by sequence
alignment via the modified Needleman-Wunsch algorithm. The focused and
iterative search step aims to improve the performance of the object detection
and planogram compliance control steps. We tested all three steps on two
different datasets. Based on these tests, we summarize the key findings as well
as strengths and weaknesses of the proposed method.
