Software that adapts its behavior to an operational context and/or feedback from within is self-adaptive. For instance, a computer vision system to detect people may change its behavior due to change in context such as nightfall. This may entail automatic change in architecture, software com- ponents and their parameters at runtime. Legacy software components do not possess this ability. Therefore we ask, can legacy software be successfully cast into a self-adaptive middleware framework ? We present Tekio, a self-adaptive middleware platform to dynamically compose legacy soft- ware behavior. Tekio is based on dynamic component load- ing available in a Java implementation of Open Service Gate- way Interface (OSGi). Tekio contains generic components to capture context/feedback, plan an adaptation strategy, and reconfigure domain-specific components. The domain- specific components encapsulate legacy behavior implemented possibly in native languages such as C/C++. We implement a self-adaptive vision system in Tekio as a case study. We perform experiments to validate that the self-adaptive layer based on OSGi has negligible effects on the performance of the legacy library namely OpenCV. We also demonstrate that the self-adaptive middleware can handle about 30 adap- tations in a span of 2 seconds while producing meaningful output.