Object-based retrieval is a modality for video retrieval based on segmenting objects from video and allowing end-users to use these objects as part of querying. In this paper we describe an empirical TRECVid-like evaluation of object-based search, and compare it with a standard image-based search into an interactive experiment with 24 search topics and 16 users each performing 12 search tasks on 50 hours of rushes video. This experiment attempts to measure the impact of object-based search on a corpus of video where textual annotation is not available.